Data Analysis Projects on Upwork Efficiently

I’m looking for hands-on guidance that will strengthen my technical toolkit specifically in statistical analysis. My aim is to move beyond simply running canned tests and instead understand the “why” behind each method, interpret results confidently, and apply them to real-world data sets.

Here’s what I have in mind:
• A clear learning plan that starts with core concepts (descriptive statistics, hypothesis testing, confidence intervals) and progresses into more advanced topics such as regression, ANOVA, and multivariate techniques.
• Live or recorded walkthroughs of each concept using widely-used tools—Excel, Python (pandas, SciPy, statsmodels) or R—whichever you feel most comfortable teaching.
• Practical exercises with sample or client-supplied data, followed by detailed feedback on my approach, code, and interpretation.
• Short quizzes or mini-projects to track my progress and highlight areas that need reinforcement.
• A final capstone task where I choose a dataset, design the analysis end-to-end, and receive a comprehensive review from you.

Please let me know:
1. Your preferred software/platform for demonstrations.
2. How you structure tutoring sessions (length, frequency, and typical timeline).
3. Any previous teaching or mentoring experience that shows you can break down complex statistical ideas into clear, actionable steps.

I’m ready to start as soon as we align on a schedule and roadmap.

Skills: Excel, Statistics, SPSS Statistics, Pandas

I need to build a AI tool which will help me during the interview. As in listening and spitting out answers. Let me know if you have any questions.

We are looking for an experienced Full Stack Developer for AI/LLM Integration with strong expertise in healthcare, life sciences, and regulated environments.

The ideal candidate has hands-on experience taking AI features to production in healthcare platforms: integrating LLM APIs, migrating workloads to HIPAA-eligible infrastructure, and ensuring compliance, security, and operational reliability under real user volume.

Requirements:

- 8+ years of software engineering experience
- Strong TypeScript and Node.js expertise (Express, tRPC, REST APIs)
- Python for AI/ML workflows where needed
- Experience with AWS Bedrock, Anthropic, OpenAI, or similar AI platforms
- AI API integration and LLM implementation experience (streaming, prompt/output validation, cost and latency tuning)
- Healthcare, payer, pharma, or clinical technology background
- Experience working with HIPAA-compliant systems (BAA-covered data flows, audit logging, session security)
- Strong API architecture and backend development skills
- Experience stabilizing and extending existing production codebases, including AI-generated code

Nice to Have:

- CMS-regulated healthcare experience (prior authorization, utilization management, claims, risk adjustment, care management)
- Clinical trials, pharmacovigilance, or GxP-validated systems
- RAG systems, embeddings, and document extraction pipelines
- React frontend experience
- AWS (RDS, S3, Secrets Manager), Docker, CI/CD
- MySQL or PostgreSQL with ORM migrations (Drizzle, Prisma)

Responsibilities:

- Design and implement AI-powered healthcare workflows
- Integrate LLM APIs into existing software platforms and migrate off non-compliant vendors
- Build secure and scalable backend services and APIs
- Advise on AI architecture, HIPAA data flows, and production deployment
- Implement audit logging, access controls, and regression test coverage
- Ensure reliability, compliance, and maintainability of AI solutions

Please include examples of healthcare AI, clinical technology, payer systems, or other regulated-industry projects you have worked on.

I have completed a study on the insecticidal potential of essential-oil-based formulations used to protect stored dates and now need it shaped into a publishable scientific article. You will start from my raw research notes, data tables and lab photographs to craft a full manuscript and deliver the finished work as a clean, submission-ready PDF.

The article must read like a peer-reviewed paper: concise abstract, clear introduction, well-structured materials and methods, rigorously presented results, and a solid discussion that integrates statistical analysis with current literature. I want all three pillars—methodology, experimental results and data analysis—developed in depth so reviewers can replicate and critique the work with confidence.

Because the subject sits at the crossroads of post-harvest technology and green pest control, please weave in recent citations on essential oils, fumigation alternatives and date-fruit conservation. Graphs, dose–mortality curves, and any factorial ANOVA outputs should be rendered with professional clarity (R, Python or Origin—your choice—as long as figures are high-resolution and embedded directly in the PDF).

Deliverables
• One publication-ready PDF manuscript (≈6,000–8,000 words) following a standard journal template (e.g., Elsevier or Springer format)
• Editable source file (Word, LaTeX or equivalent) so I can adapt to different journal guidelines
• Separate folder containing high-resolution figures and the cleaned data set used for analyses

Acceptance criteria: the paper passes iThenticate (<10 % similarity), references are formatted consistently, statistical tests match the described methodology, and all claims are supported by data or citations.

If you have experience publishing in food science, entomology or natural-product chemistry journals, you’ll feel at home with this project.

Skills: Statistics, Research Writing, Statistical Analysis, SPSS Statistics, Academic Writing, Data Visualization, Data Analysis, Scientific Writing

Description
We're a direct-to-consumer (DTC) e-commerce business looking for an experienced Tableau developer to build a single, auto-refreshing dashboard that consolidates our marketing and sales data into one clear view the team checks every morning.

What we're building

One Tableau dashboard that brings together Meta Ads, Google Ads, Shopify, email (Klaviyo), and organic search — with a simple top-line summary over a detailed breakdown. It must refresh automatically each day with little to no manual work, and be easy to export (PDF/Excel).

We're delivering this in two phases:

Phase 1 (core — needed by ~September 1): revenue, orders, AOV, ad spend, ROAS (blended and by paid channel), CAC, and new vs. returning customers.
Phase 2 (follow-on): full per-channel detail (CTR, CPM, impressions), organic search, email engagement, customer LTV/cohorts, trends, and alerting.

Note on existing data

We previously had a Tableau dashboard built by another contractor. While the visualization/dashboard itself isn't transferable, we do have (or can obtain) an export of the underlying backend data that fed it. This won't replace the need to set up a live, auto-refreshing pipeline, but it may help you get oriented faster on our historical data structure and metrics, and could be useful for backfilling historical trends. We're happy to share this export with the selected contractor once we begin.

The core technical challenge — the data pipeline

The dashboard itself is the easy part. The real work is getting Meta, Shopify, Google Ads, email, and Search Console data flowing automatically into Tableau and staying reliable. Keeping ongoing costs lean is a priority for us — we want you to recommend and set up the most cost-effective, low-maintenance connector approach (e.g., Windsor.ai, Supermetrics, or a lightweight warehouse), and tell us the expected monthly cost up front.

Data sources

Meta Ads — spend, impressions, clicks, attributed revenue
Google Ads — paid search spend, clicks, conversions
Shopify — orders, revenue, AOV, new vs. returning customers
Email (Klaviyo) — sends, engagement, attributed revenue
Google Search Console — organic clicks, impressions, CTR (Phase 2)

Deliverables

A working, documented Tableau dashboard (Phase 1) with the metrics above
Automated daily data refresh (no manual pulls)
A recommended connector/pipeline setup with a clear ongoing cost breakdown
Documentation and handoff so our team can maintain it without you
Phase 2 available as a follow-on engagement for the right person

Required skills & experience

Proven Tableau experience (Desktop + Cloud/Server): blended data sources, calculated fields, scheduled extracts/refresh, publishing and access control
Hands-on marketing data pipelines — Windsor.ai, Supermetrics, Fivetran, or similar
Direct experience with the source platforms individually: Meta Ads, Google Ads, GA4, Google Search Console, Shopify, Klaviyo (their APIs and data quirks)
Strong grasp of DTC/e-commerce metrics: ROAS, blended ROAS (MER), CAC, AOV, LTV
Marketing attribution literacy — able to reconcile differing revenue numbers across platforms and help us define one source of truth
Clear documentation and a clean handoff

Nice to have

SQL / light data warehousing (BigQuery or similar)
Prior DTC / e-commerce brand experience
A track record of keeping tooling and costs lean

Marketing Data Analyst — Lifecycle Marketing Analytics & Reporting
About the Project

I’m looking for a Marketing Data Analyst with strong SQL skills and lifecycle/CRM marketing experience to help build a reusable reporting and measurement framework for lifecycle marketing clients.

I work with companies using platforms such as Braze and Customer.io, with customer and event data typically available in BigQuery / SQL data warehouses.

The goal is not simply to build a dashboard.

I want to create the underlying data model, metric definitions, and reporting structure that allows us to understand:

Who lifecycle marketing is reaching
Which customer segments are receiving lifecycle communications
How those segments are behaving and converting
How lifecycle campaigns influence conversion
Where there are gaps or opportunities within the customer journey
How performance changes over time

The ideal person can take relatively messy marketing + product data and turn it into a clean measurement framework that can eventually power dashboards, recurring reports, and strategic lifecycle recommendations.

What You'll Help Build
1. Lifecycle Reporting Data Model

Design the underlying SQL/data structure needed to analyze lifecycle marketing performance.

This may include combining:

Customer/user data
Product/event data
Braze or Customer.io messaging data
Campaign and journey participation
Email sends, opens, clicks
SMS/push/in-app messaging
Conversion events
Customer lifecycle stages and segments

The goal is to create reliable datasets that can be queried repeatedly rather than rebuilding analyses from scratch.

2. Metric & Measurement Framework

Help define consistent lifecycle marketing metrics and their calculation methodology.

Examples include:

Total Reach Rate (TRR)
What percentage of eligible/active customers are being reached by lifecycle marketing over a defined period?

We would want to understand reach by:

Lifecycle stage
Customer segment
Channel
Campaign/journey
Week/month
Message frequency

Segment Conversion

For each important customer segment:

Number of users
Number reached
Number engaged
Number converted
Conversion rate
Conversion rate among reached vs. unreached users
Conversion by campaign/journey exposure
Time to conversion
3. Lifecycle Segment Analysis

Create a framework for analyzing customers based on lifecycle behavior.

For example:

Acquisition → Activation → Engagement → Retention → Resurrection

Within those stages, we may have behavioral segments such as:

Signed up but not activated
Activated but not engaged
Engaged but not using a key feature
High-intent users who haven't converted
Previously active users becoming dormant
Churned users who could potentially be resurrected

We want to be able to answer:

How many customers are in each segment?

What percentage are currently being reached by lifecycle marketing?

What percentage convert naturally?

What percentage convert after lifecycle exposure?

Which segments represent the largest conversion opportunities?

4. Conversion Opportunity Analysis

One of the most important outcomes of this project is identifying where lifecycle marketing should focus next.

The reporting should help us distinguish between:

Reach problems — we aren't communicating with enough of the segment
Conversion problems — we're reaching them, but they aren't converting
Journey gaps — there is no lifecycle campaign addressing the behavior
Targeting opportunities — certain behavioral segments significantly outperform others
Initial Deliverables

For the first engagement, I would expect something along the lines of:

Audit available lifecycle, customer, and conversion data
Recommend lifecycle reporting architecture
Define core metrics and calculation methodology
Define lifecycle segments and reporting dimensions
Build the underlying SQL queries / data models
Create documentation/data dictionary for the framework
Produce an initial analysis demonstrating the framework
Recommend how the data should eventually be surfaced in dashboards

I'm particularly interested in creating a framework that can be adapted across multiple lifecycle marketing clients, rather than building something completely custom every time.

Ideal Background

You may be a strong fit if you have experience with:

Advanced SQL
BigQuery
Marketing analytics
Lifecycle / CRM analytics
Braze and/or Customer.io
Customer journey analysis
Cohort analysis
Funnel analysis
Segmentation
Conversion analysis
Marketing attribution/measurement
Data modeling

Experience working with subscription businesses, fintech, SaaS, marketplaces, apps, or high-volume B2C companies would be especially useful.

You do not need to be a lifecycle marketing strategist — I will own the lifecycle strategy.

I need someone who can translate the strategic questions I want to answer into a technically sound data and measurement framework.

What I'm Looking for in Your Proposal

Please include:

An example of a lifecycle/CRM/customer analytics framework you've built.
How you would approach measuring conversion among users who were reached by lifecycle marketing versus those who weren't.
How you would structure data to analyze conversion across behavioral customer segments.
Your experience working with Braze and/or Customer.io data.
Your experience with BigQuery and SQL.

If you've built reporting that connects marketing communication → customer behavior → downstream conversion, please describe that project.

Summary
We are seeking a skilled Data Analyst to help us optimize our food processing operations, track production metrics, and build interactive dashboards. The ideal candidate will transform raw manufacturing, inventory, and distribution data into actionable insights using Excel, SQL, and Power BI to support quality control, yield improvement, and smarter business decisions.

Project Scope

Data Cleaning & Prep: Clean, organize, and validate raw datasets from plant sensors, inventory systems, and yield logs.

Operational Analysis: Analyze production trends, batch cycle times, scrap rates, and key operational KPIs (e.g., OEE, waste reduction, throughput).

Database Querying: Write efficient SQL queries to extract, blend, and manipulate data across production, warehouse, and sales databases.

Advanced Excel Modeling: Build Excel workbooks using advanced formulas, pivot tables, XLOOKUPs, and data validation to model batch costs and daily outputs.

Dashboard Creation: Design intuitive Power BI dashboards with interactive visual features to track plant performance, inventory turnover, and quality metrics in real time.

Actionable Insights: Translate complex operational data into clear, high-level business recommendations for plant managers and executive leadership.

Documentation: Deliver clean code, well-organized project files, and dynamic reports.

Requirements

Proven experience as a Data Analyst, preferably with exposure to manufacturing, supply chain, consumer packaged goods (CPG), or food processing environments.

Strong proficiency in Microsoft Excel for complex data manipulation.

Solid knowledge of SQL for querying relational databases.

Hands-on experience building interactive dashboards in Power BI.

Strong analytical, problem-solving, and process-oriented mindset.

Exceptional attention to detail and ability to communicate findings clearly to non-technical operational teams.

Ability to hit deadlines while maintaining strict data integrity.

Deliverables

Cleaned and structured operational datasets.

Documented SQL queries used for data extraction and transformation.

Excel analysis workbooks (yield models, scrap analysis, or cost breakdowns).

Interactive Power BI plant/production dashboard.

Executive summary report outlining key operational findings and optimization recommendations.

AI Trading Engineer / Algorithmic Trading Developer for Automated Financial Markets System
I am looking for a highly experienced developer and potentially a long-term technical partner to help me build and continuously improve an AI-powered automated trading system for financial markets.
The system should be designed to analyze and trade different financial markets, including stocks, commodities, indices, Forex and potentially other asset classes. Silver (XAG/USD) is one of the markets I am particularly interested in, but it is not limited to silver.
The goal is to turn my own trading ideas and strategies into a professional, scalable and automated system that can analyze market data, identify potential opportunities, manage risk and, after extensive testing, potentially execute trades automatically.
I am looking for someone with strong knowledge in:
Financial markets and trading
Algorithmic and quantitative trading
Technical analysis and market data
Risk and money management
Python and software development
APIs and broker integrations
AI/LLMs and AI-assisted development
Backtesting and strategy optimization
Cloud infrastructure and automated systems
The project may include:
Development of an AI-powered trading platform
Automated analysis of stocks, commodities, indices, Forex and other markets
Implementation of my own trading ideas and strategies
Development and testing of algorithmic trading strategies
AI-assisted market analysis
Real-time market data processing
Historical data analysis and backtesting
Risk management and position sizing
Automated stop-loss and take-profit systems
Broker/API integrations
Automated order execution
Portfolio management
Trade monitoring and logging
Dashboard for monitoring the system
Cloud deployment and reliable 24/7 operation
Modular architecture so that new markets and strategies can easily be added
I am not looking for someone to simply install an existing trading bot or copy an existing strategy.
I want to build a custom system based on my ideas, with the developer contributing their own technical and financial expertise to improve the concept.
I can provide the necessary software, AI tools, cloud infrastructure and premium subscriptions required for development. This may include access to premium AI coding environments such as Claude Code or comparable AI development tools, as well as other software, APIs and services required for the project.
I am particularly interested in someone who understands AI-assisted and agentic software development and knows how to use modern AI coding tools effectively to build, test, debug and improve complex software systems.
I am looking for someone who thinks independently, understands financial markets, challenges ideas when necessary, proposes solutions and can turn concepts into reliable software.
This is intended to become a long-term collaboration. The goal is not simply to build one trading strategy, but potentially to develop a complete trading system that can continuously evolve and support multiple markets and strategies.
Please include in your application:
Your experience with algorithmic or automated trading.
Examples of trading systems, bots or financial software you have developed.
Your experience with stocks, commodities, indices, Forex, futures, CFDs or other financial markets.
Your experience with Python, APIs, databases and cloud infrastructure.
Your experience with AI/LLMs and AI coding tools.
Examples of previous projects, GitHub or portfolio, if available.
Which brokers, exchanges and trading APIs you have worked with.
Your hourly rate or estimated project cost.
Whether you are interested in a long-term collaboration.
Important: The system will initially be developed and tested exclusively in a paper-trading/simulation environment. Real-money trading would only be considered after extensive backtesting, validation and technical testing.
I am looking for someone who can become a technical and strategic partner for this project, rather than simply a developer who follows instructions.

Skills: Python, Cloud Computing, Machine Learning (ML), Data Analysis, API Development, API Integration, AI Model Development, AI Development, AI Integration, AI Automation

Hey man, I need your help putting together a custom tactical map sheet. We are building a true 1:50,000 scale military map using a combination of provided aerial/satellite images, an external data file, and reference coordinates pulled from MilGPS.
It needs to meet exact U.S. military specifications and doctrine (per TC 3-25.26) so it functions precisely like an issue map in the field. Please review these exact build parameters and execute the layout accordingly:
⚬ Scale & Proportions: Must be an exact 1:50,000 ratio (where 2 cm on the map equals 1 km on the ground) to maintain standard tactical distance measuring without distortion.
⚬ Grid System: Integrate a full Military Grid Reference System (MGRS) grid overlay based on the provided MilGPS data, utilizing standard 1,000-meter grid squares.
⚬ Marginal Data Requirements: Include proper marginal information layout—specifically the bar scales (meters, statute miles, nautical miles), contour interval notes, declination diagram (showing True North, Magnetic North, and Grid North relationships), and the sheet name/number identification block.
⚬ Standard Topographic Colors: Adhere strictly to standard military cartographic coloring rules:
⚬ Black: Man-made features, structures, and grid labels.
⚬ Red-Brown: Contour lines, elevation data, and relief features optimized for red-lens tactical lighting.
⚬ Blue: Hydrography (lakes, streams, swamps).
⚬ Green: Vegetative cover with tactical significance.
⚬ Contour & Elevation Standards: Ensure contour lines correctly reflect terrain features (hills, ridges, valleys, saddles, depressions with hachures) matching the elevation profile derived from the source files.
Lastly, it MUST abide by these Core Governing Documents and Standards
⚬ TC 3-25.26 (formerly FM 3-25.26) — Map Reading and Land Navigation: The foundational U.S. Army and joint-service manual covering map utilization, marginal data layout, MGRS grid rules, topographic symbols, and terrain association.
⚬ MIL-STD-2400 — Department of Defense Interface Standard for Vector Product Format (VPF): Governs the structural and relational data standards for digital vector maps used by military command and control systems.
⚬ MIL-PRF-89033 / MIL-PRF-89038 — Performance Specifications for Topographic Line Maps (TLM): The strict NGA manufacturing specifications detailing how standard 1:50,000 scale paper and digital line maps must be styled, projected, and printed.
⚬ National System for Geospatial Intelligence (NSG) Standards: A collection of interoperability and data-exchange standards enforced across the Army Geospatial Enterprise (AGE) and NGA to ensure all tactical systems interpret terrain coordinates identically.
⚬ NGA GEOINT Basic Doctrine (Pub 1.0): Establishes the overarching framework and foundational principles for how geospatial intelligence, elevation models, and operational maps are produced and applied across national security missions.
⚬ WGS 84 (World Geodetic System 1984) / NTM (NGA Framing Standards): The mandated mathematical reference ellipsoid and coordinate system standard (Department of Defense World Geodetic System) required for all military GPS receivers, mapping software, and targeting layers.
Let me know when you can pull the source files together and get a draft over. Appreciate it.

Quiero automatizar por completo mi cuenta de WhatsApp Business con un enfoque claro en aumentar las ventas. Necesito que configures tres pilares de la comunicación:

• Respuestas rápidas para preguntas frecuentes, de modo que cualquier consulta habitual quede atendida al instante y sin errores.
• Mensajes de bienvenida que generen cercanía y presenten de forma breve nuestras ofertas o servicios desde el primer contacto.
• Recordatorios automáticos capaces de reactivar conversaciones o cerrar ventas pendientes, según el momento óptimo que tú mismo definas.

El objetivo es que cada uno de estos mensajes fluya de forma coherente dentro de un embudo comercial sencillo, aproveche las etiquetas y plantillas oficiales de WhatsApp Business API y, si es viable, se integre con nuestro CRM o con herramientas como Zapier o Meta Cloud API para registrar datos y medir resultados.

No tengo prisa estricta por la entrega, así que priorizo la calidad y la escalabilidad de la solución sobre la velocidad. Al finalizar, espero:

– Flujos configurados y probados en mi cuenta real.
– Documentación breve que indique cómo ajustar textos o tiempos si más adelante cambian las necesidades.
– Sugerencias de buenas prácticas para seguir optimizando ventas a través de WhatsApp.

Si necesitas información adicional sobre el negocio, métricas actuales o acceso a sistemas, indícalo y lo preparo.

Skills: CRM, Digital Marketing, Data Analysis, Lead Generation, Automation, Zapier, API Integration, Chatbot Development

Bankura Urban Development: From Challenges to Opportunities
Infrastructure Gaps → Integrated Infrastructure
Upgrade roads, drainage, water supply, sanitation and public utilities through coordinated planning.
Impact: Better services, connectivity and quality of urban life.
Traffic & Mobility Pressure → Smart & Sustainable Mobility
Improve public transport, pedestrian facilities, parking management and strategic road connectivity.
Impact: Reduced congestion, safer mobility and stronger urban connectivity.
Water Stress → Water-Secure Bankura
Promote rainwater harvesting, water-body restoration, leakage reduction and sustainable groundwater management.
Impact: Reliable water availability and long-term water security.
Waste Management Challenges → Circular Waste Economy
Introduce source segregation, efficient collection, composting, recycling and scientific waste processing.
Impact: Cleaner cities, resource recovery and reduced environmental pressure.
Unplanned Expansion → Planned Urban Growth
Use GIS-based land-use planning, development corridors and protected green/open spaces.
Impact: Controlled expansion and more efficient use of land.
Limited Urban Employment → Local Economic Growth
Strengthen MSMEs, local markets, handicrafts, tourism, services and skill-development ecosystems.
Impact: More employment, entrepreneurship and local economic opportunities.
Heritage Potential → Heritage-Led Urban Regeneration
Connect heritage, culture, crafts and tourism with improved public spaces and visitor infrastructure.
Impact: Tourism growth, local income and preservation of cultural identity.
Environmental Pressure → Green & Resilient Urbanism
Expand urban greenery, conserve water bodies, improve drainage and promote climate-sensitive infrastructure.
Impact: Greater climate resilience and healthier urban environments.
Social Infrastructure Gaps → Inclusive Urban Services
Improve equitable access to healthcare, education, recreation, housing and community facilities.
Impact: More inclusive and liveable urban settlements.
Fragmented Planning → Data-Driven Governance
Establish GIS-based urban monitoring, digital service delivery, periodic infrastructure audits and citizen participation.
Impact: Faster decisions, better resource allocation and accountable governance..

Skills: Graphic Design, Photography, Data Analysis, Urban Design, Urban Planning, Public Health

We need a reliable freelancer to enter and organize real estate data into spreadsheets with accuracy and consistency. The work includes updating property records, entering listing details, and maintaining clean, error-free spreadsheets. You should be comfortable handling repetitive data tasks, following instructions carefully, and working independently. This is a part-time opportunity for someone who can manage data entry efficiently and help keep records organized over time.

Skills: Data Processing, Data Entry, Excel, Web Search, Data Cleansing, Data Analysis, Data Management, Data Annotation

We need a freelancer to clean and organize SQL data for a reporting dashboard, then build a clear Excel-based analysis and a Power BI dashboard. The work includes reviewing the data, identifying and resolving inconsistencies, preparing a structured dataset, and creating reports that are easy to understand and update. You should be able to translate raw data into actionable insights and deliver a polished final product that supports ongoing reporting needs.

We are looking for an SQL expert who can help build business dashboards and consolidate all the moving pieces into one single database

I want an experienced business data analyst who can solve my excel assessment and also document each and everything happened and solution step by step

Skills: Python, Excel, Statistics, Research Writing, Business Analysis, Statistical Analysis, Documentation, Data Visualization, Data Analysis, Predictive Analytics

I have a data sample of bank information and i have a task on power bi to turn these data into visuals i will download the data and the target result information please let me know if u can help and i need it as soon as possible

I need an end-to-end Tableau dashboard that puts sales performance front and center. The data set is ready; what I’m missing is the polished, interactive layer that lets managers explore results on their own.

Here is what matters most to me:
• Key metrics: Total sales and Sales by product must be clearly surfaced, with room to add growth rate later if we decide it’s useful.
• Visuals: Combine Bar, Line, and Pie charts so users can switch perspectives without leaving the workbook.
• Interactivity: Filters by region, product category, and time period, plus hover tooltips and drill-downs that reveal underlying tables.
• Storytelling: A concise KPI banner that highlights highs and lows at a glance before users dive deeper.

Deliverables
• A packaged Tableau workbook (.twbx) and a brief walkthrough video or PDF explaining how each element works.
• Any calculated fields or data-prep steps documented so I can refresh the dashboard with new data.
• One round of feedback incorporated after I test the dashboard with stakeholders.

Skills: JavaScript, Visual Basic, Excel, Powerpoint, Tableau, Business Intelligence, Data Visualization, Data Analysis

About the Project

We're building, an AI-powered equity research application. The product surfaces financial data, analysis, and insights for retail and semi-professional investors, combining structured market data with LLM-driven synthesis. We're looking for a full-stack developer who can own both the application layer and the AI/data integration layer, working directly with the founder.

This is a build-from-the-ground-up engagement with room to grow into an ongoing role if there's a strong fit.

What You'll Do:

- Architect and build the core application: frontend, backend, database, and API layer
Integrate financial market data providers (e.g., pricing, fundamentals, filings, news feeds)
- Build LLM-powered features — research summarization, Q&A over financial data, report generation — using the Anthropic/OpenAI API or similar
- Design data pipelines that clean, structure, and cache financial data for fast retrieval and AI consumption
- Implement authentication, user accounts, and (eventually) subscription/billing infrastructure
- Write clean, documented, maintainable code and make sensible architecture decisions with cost and scalability in mind
- Collaborate directly with the founder on product scope and priorities

The problem is similar to

1.) A stack is growing in real-time in a Variable Rate, items/sec.

2.) But rate varies as it grows. for instance from 0 to 100 it's slow , from 100 to 250 rate is higher and it peaks around 350 and starts dropping after that point.

3.) And i want to place myself at position 300.

4.) There is a latency when i trigger an add operation. let's say 2secs.

5.) When or at what position should i trigger this add operation to be able to add myself as close to position 300 ?

We have correction functions like sigmoid and bell curve running already. But a mathematician come up with a better way or simulate some function or functions to be able to test them.

Looking for someone to analyze the data samples and to come up with function or functions best to apply.

And if you could come up with a simulator to apply those functions to historical data, or a way to test them, that would be nice.

I have a collection of permit documents that need to be mined for specific information—permit number, property address, applicant details, dates, and any notes that appear on the forms. Once captured, every field must be organised in a clean, well-structured Excel workbook.

Most of the permits follow a consistent layout, but there can be slight variations from file to file. I will supply a small sample set upfront so you can confirm the parsing logic before processing the full batch. OCR or other text-recognition methods may be required if any pages are embedded as images rather than selectable text; I’m open to whichever approach maintains accuracy above all.

Deliverables
• One Excel file (.xlsx) containing a separate row for each permit and clearly labelled columns for every captured field
• A brief outline of the extraction method (manual, scripted, or hybrid) so I understand how the data was obtained and can replicate or audit the process later

Please keep an eye on spelling, date formats (YYYY-MM-DD), and consistent street abbreviations. The project is complete once the spreadsheet passes a quick spot-check against random source files for 100 % accuracy in the sampled rows.

Skills: Visual Basic, Data Processing, Data Entry, Excel, OCR, Data Extraction, Data Analysis, Data Management

We are looking for a skilled and motivated Data Analyst with Ambitions to learns new skills sets. This is a great opportunity to join our growing company and make a real impact.

Responsibilities
• Clearing claim prevention and Spot checking claims before they are submitted to HMRC
• Supporting the team with client scanner installs training and support.
•. Data Entry, spreadsheets.

Skills and Experience
• Ability to work on own initiative and under pressure.
• Previous experience working in an office environment is preferred.
• Great IT skills, specifically in the use of Microsoft Office (Word, Excel, Access, Outlook).
• Ability to work responsibly to effectively prioritize and execute tasks.
• Excellent attention to detail and good communication skills.

The above is a mini brief of some of the tasks you will be involved in. We work in an active way, and you might be involved in lots of different tasks.

Our services in brief
GoodtoGive empowers faith-based charities to flourish by giving them access to the financial resources and freedom needed to continue the vital work that fuels their purpose. Our goal is to enable charities like yours to harness the potential of Gift Aid - unlocking additional financial support that can significantly propel your initiatives forward.

We alleviate the cumbersome administrative burden that Gift Aid management used to signify. Our effortless process and intuitive platform take the complexity out of Gift Aid.
Through our unique Gift Aid maximisation process, we are able to reach back into your Gift Aid history and make claims retrospectively, as far back as 4 years. Ensuring that no Gift Aid income goes unclaimed

I am in need of a detail-oriented freelancer to assist with processing over 201 invoices using Tally Prime. This project requires someone with a strong background in data entry and familiarity with Tally Prime for efficient and accurate invoice management.

Key Requirements:
- Process and enter over 201 invoices into Tally Prime
- Ensure accuracy and completeness of all data entries
- Maintain confidentiality and integrity of financial information

Ideal Skills and Experience:
- Proficiency in Tally Prime for accounting tasks
- Experience in invoice processing and data entry
- Strong attention to detail and organizational skills
- Ability to work efficiently with large volumes of data

If you have the expertise and experience in handling invoice processing with Tally Prime, I would love to hear from you.

Skills: Data Processing, Data Entry, Accounting, Excel, Financial Analysis, Bookkeeping, Data Analysis, Data Management

We are seeking a detail-oriented freelancer to evaluate various consumer sport products purchased online. Your primary task will involve testing the products and providing comprehensive written feedback based on your experience through the Upwork platform. This feedback will be invaluable in enhancing product quality and customer satisfaction. If you have a knack for detail and a passion for products, we want to hear from you! This job will be in compliance with Upwork's Terms of Service.

HIPAA Expert Determination Specialist - Healthcare Data De-identification

We need a qualified expert to perform a formal HIPAA Expert Determination to deidentify and anonymize our dataset.

What You'll Do
- Assess re-identification risk
- Design a de-identification strategy including:
- Perform formal statistical risk analysis and produce a regulatorily defensible Expert Determination report

Required
- PhD or equivalent in statistics, biostatistics, epidemiology, or related quantitative field
- Proven track record completing HIPAA Expert Determinations (submit 2+ examples)
- Deep expertise in re-identification risk assessment
- Familiarity with behavioral health data and 42 CFR Part 2

Deliverables
- Signed Expert Determination report
- 1-2 hours of handoff consultation with our data engineering team

to apply Include your credentials, 2+ prior Expert Determination examples (anonymized is fine), your proposed approach to our specific challenges, and your estimated fee/timeline.

We need a data-driven shortlist of gyms, sports clubs, leisure centres and similar venues across London that plausibly have spare indoor or outdoor space (rooftop, plant room, unused changing area, yard, car park) where we could install a sauna and cold plunge under a rental/revenue-share agreement.

Background

Lowlu operates sauna and cold plunge venues in London (currently North London Sauna in Kentish Town and The Padel Yard in Wandsworth). We're looking to expand by partnering with existing sports and fitness venues that have underused space, rather than building standalone sites from scratch.

What we need from you

Build a target list of London venues in scope: gyms, health clubs, sports clubs, leisure centres, padel/tennis/squash clubs, swimming pools, hotels with spas, members' clubs.

Roughly 150–300 candidates to start, ranked by fit.

Enrich each site with the data needed to prioritise outreach — as available:
- Address, postcode, borough, operator/owner name, contact info if findable
- Approximate site footprint and building footprint (from OS/EPC data)
- Rateable value & floor area band (VOA business rates data)
- Indicative outdoor space or rooftop area, and roof aspect/slope where relevant (Environment Agency LiDAR) — useful for cold plunge/outdoor sauna setups, not a hard requirement
- Any signals of spare capacity: e.g. underused car park, disused pool plant room, recent planning applications, To-Let/space-share listings
Nearby footfall/catchment indicators (population density, income profile) as a rough demand proxy
- Deliver as a spreadsheet + simple map (e.g. CSV/Excel plus a Google My Maps, QGIS, or ArcGIS Online layer) so we can filter, sort, and drop pins as we do outreach.
- Flag data gaps honestly — where "spare space" can't be confirmed from public data, say so rather than guessing; we'll verify manually once we reach out.

What "good" looks like

A short, credible list beats a huge noisy one. We'd rather have 150 well-qualified, correctly-categorised venues with a clear reason each made the list than 1,000 scraped names. Please include your source/method for each data field so we can sanity-check it.

Suggested approach / data sources (use your judgement — you may know better ones)

Venue universe: Google Places / OpenStreetMap POIs, Companies House (SIC codes for sports facility operation), London Datastore
Site & building data: OS Open Data / OS MasterMap, EPC register (floor area), VOA business rates list (use class + rateable value)
Roof/outdoor space: Environment Agency LiDAR (for aspect/slope where rooftop space matters)
Ownership/lease signals: Land Registry, planning portal applications, commercial property listings (Rightmove Commercial, EG Propertylink)

Scope & format

One-off engagement, freelance/contract basis
Deliverable: spreadsheet (CSV/XLSX) with one row per venue and the fields above, plus a map view



Who this suits

A freelance GIS analyst, geospatial data consultant, or location-intelligence researcher comfortable combining public UK geospatial/property datasets with some manual research and judgement calls — this is part data pull, part detective work, not a pure GIS engineering task.

# RudderStack → PostHog & Grafana Product Analytics / BI Specialist

## Overview

We are looking for an experienced **RudderStack + PostHog + Grafana analytics specialist** to help us turn our web and mobile application events into useful, easy-to-understand business intelligence and observability dashboards.

Our data flow is:

**Web / iOS / Android → RudderStack → PostHog + Grafana**

The goal is to create reliable, well-organized analytics that help Product, Engineering, and Leadership understand what users are doing, quickly identify unusual behavior, and maintain everything independently after the engagement ends.

## Scope of Work

### Foundation & Data Quality

* Review our existing RudderStack event data and our PostHog and Grafana setup and configuration.
* Help define which events and metrics are actually worth monitoring.
* Improve event naming, properties, and organization where needed.
* Troubleshoot issues with events, data flow, queries, and visualizations.
* Recommend improvements to dashboard structure, queries, data models, and visualization approach.

### PostHog — Product Analytics & BI

* Organize and visualize important product events and user behaviors in PostHog.
* Build dashboards for key business/product metrics, including:
* User activity and engagement
* Conversion and funnel metrics
* Feature usage
* Video/content engagement
* Errors or unusual event patterns
* Web vs. mobile behavior
* Other important BI metrics identified during the project
* Configure **thresholds and anomaly alerts** for important metrics so we can identify significant changes or unexpected behavior.
* Create simple, executive-friendly dashboards that can be understood without technical knowledge.

### Grafana — Engineering & Advanced Visualization

* Build and improve Grafana dashboards for product and engineering analytics.
* Create advanced visualizations, especially **Sankey diagrams**, funnels, trends, distributions, and other useful charts.
* Model and visualize event data coming from RudderStack.
* Establish reusable dashboard/query patterns that our engineers can maintain.

### Documentation

* Document the dashboards, metrics, alert definitions, queries, and best practices.

## Knowledge Transfer — Required

This is **not just a dashboard-building project**.

You will work directly with our team — both technical and non-technical — and **teach them how to do this themselves**. For each piece of work, the goal is to leave behind enough knowledge, documentation, examples, and best practices for our team to reproduce, maintain, and extend the dashboards, metrics, and alerts independently.

Knowledge transfer should become part of our **Definition of Done (DoD)** for analytics/dashboard tickets.

## Ideal Candidate

* Strong hands-on **PostHog** experience.
* Strong hands-on **Grafana** experience, including Sankey diagrams and advanced visualizations.
* Strong **RudderStack** experience, including event tracking and data pipelines.
* Strong SQL/data analysis skills.
* Experience working with web and mobile product analytics and event data.
* Strong understanding of product/business metrics and BI dashboards.
* Experience defining meaningful KPIs, funnels, and anomaly thresholds.
* Able to turn raw event data into simple, actionable insights.
* Excellent communication and training skills — able to explain technical concepts clearly to both software engineers and non-technical stakeholders.

## Deliverables

1. PostHog analytics dashboards (product/BI metrics, funnels, user-behavior analysis).
2. Improved/new Grafana dashboards with advanced visualizations (Sankey diagrams, funnels, trends, distributions).
3. Anomaly thresholds and alerts for key metrics.
4. RudderStack/event-tracking recommendations and fixes.
5. Reusable queries and visualization patterns.
6. Documentation, examples, and metric/alert definitions.
7. Team training and knowledge-transfer sessions.
8. A repeatable process for our team to build and maintain dashboards, metrics, and alerts independently.

Looking for an experienced academic researcher/editor to assist with the Literature Review chapter of my MA by Research thesis (Business/Consumer Behaviour).

I am not looking for someone to write my thesis. I need assistance with reviewing and verifying my literature review to ensure that every statement is accurately supported by the original academic sources.

The work includes:

Verifying that each citation supports the claim made in the text.
Reading the original journal articles and identifying unsupported or inaccurate statements.
Finding suitable replacement peer-reviewed sources where necessary.
Suggesting corrections and identifying sections that require rewriting.
Checking APA 7 referencing and citation accuracy.

The literature review is approximately 40 pages (around half of a 100-page thesis).

Experience with academic research, literature reviews, APA 7, and Business, Marketing, Consumer Behaviour, or Economics is preferred.

Please provide details of your academic background, experience with theses or dissertations, and examples of similar work.

We're looking for a Data Analyst to help transform business data into meaningful reports that support smarter decision-making across the organization.
You'll work closely with multiple departments to collect performance data, build dashboards, and identify trends that improve operational and business performance.
What you'll do
Collect KPIs from various departments.
Build dashboards and business performance reports.
Analyze sales and operational data.
Monitor marketing ROI and service retention metrics.
Prepare weekly performance summaries.
Identify reporting inconsistencies and performance trends.
You'll be a great fit if you have experience with
Data analysis and business reporting.
Building dashboards and KPI reports.
Spreadsheet and reporting tools.
Interpreting operational and sales data.
Presenting insights in a clear, actionable way.
If you enjoy turning data into meaningful business insights, we'd love to hear from you

I have a collection of raw customer datasets that needs to be explored and understood through SAS. The assignment is strictly data analysis: import the files, clean and transform them where necessary, then extract meaningful patterns and insights about customer behaviour. No dashboards or long-range forecasting are required right now—just a solid analytical deep-dive focused on the story the data tells.

You may use whichever SAS tools suit you best (Base SAS, SAS/STAT, Enterprise Guide, etc.); what matters is that the work is fully reproducible and clearly documented.

Deliverables
• Well-commented SAS programs (.sas) that run end-to-end on my side
• A short insight report (PDF or PPT) with summary tables, charts and your interpretation
• Optional: a CSV of the cleaned, analysis-ready data

Once we start I’ll share the data and a short list of business questions. Let me know your relevant SAS experience and how quickly you can turn around an initial results draft.

Skills: Data Processing, Statistics, SAS, Statistical Analysis, SPSS Statistics, Data Visualization, Data Analysis, Data Management

Project Title
MATLAB/Simulink Tutor Needed for PMDC Motor, Fan Load and PID Control Project
Project Description
I am looking for an experienced MATLAB/Simulink tutor to provide technical guidance for a university electromechanical systems project involving a permanent-magnet DC (PMDC) motor, an industrial fan load, and PID speed control.
This is a tutoring and technical-support project. I must personally complete and submit the assessed work. The freelancer should explain the modelling process, help identify errors, review my independently prepared model and results, and provide constructive feedback. The freelancer must not write or submit the final assessed report on my behalf.
Topics Covered
The project includes:
Developing a PMDC motor model in Simulink from its electrical and mechanical differential equations.
Using motor datasheet parameters such as resistance, inductance, torque/back-EMF constant, inertia and viscous friction.
Evaluating motor performance at 48 V and 90 V.
Calculating and plotting:No-load speed and current
Stall torque
Speed and current against torque
Output power and efficiency against torque
Maximum-efficiency operating point

Adding an industrial fan load with:Load inertia and damping
A nonlinear torque-speed relationship

Designing and tuning a PID controller for a specified fan-speed profile:Accelerate from 0 to 1.75 rad/s in 10 seconds
Maintain 1.75 rad/s for 80 seconds
Decelerate to 0 rad/s in 10 seconds

Evaluating controller performance, including tracking accuracy, overshoot, settling behaviour and control effort.
Discussing an appropriate position, velocity or acceleration sensor for implementing feedback control.
Required Support
The selected freelancer should:
Explain how to derive and implement the Simulink model.
Review my model structure and parameter values.
Help debug simulation errors or unexpected results.
Explain how to validate the model against the supplied motor datasheet.
Guide me through PID tuning and performance evaluation.
Review my plots, calculations and technical interpretation.
Suggest improvements while allowing me to implement the changes myself.
Provide explanations during one or more screen-sharing sessions if required.
Deliverables
Online tutoring or consultation sessions.
Written technical notes explaining the recommended modelling approach.
Feedback on my independently created MATLAB/Simulink files.
A list of identified errors and recommended corrections.
Guidance on presenting and interpreting simulation results.
No completed submission-ready report is required.
Required Skills
MATLAB
Simulink
Control Systems
PID Controller Design
DC Motor Modelling
Electromechanical Systems
Engineering Simulation
Technical Tutoring

Skills: Engineering, Electronics, Matlab and Mathematica, Technical Writing, Electrical Engineering, Signal Processing, Data Analysis, MATLAB

I’m preparing a new digital push that will rely entirely on paid social for our Smart Home Company in Dubai, UAE, with Instagram as the single channel. I already have creative assets in hand; what I need is a media-buyer who can translate those assets into tightly-targeted, conversion-oriented ad placements inside Meta’s Ads Manager.

Here’s what I want from you:
• A clear buying strategy that explains audience segmentation, bid approach, and daily spend pacing.
• Full campaign set-up inside my existing Instagram ad account (pixels, events, and any custom audiences).
• Ongoing optimisation—creative testing, budget reallocation, and bid adjustments—to keep CPA trending down.
• Weekly performance snapshots delivered in a concise report (Impressions, CTR, CPM, CPA and key recommendations).
• A wrap-up deck summarising results, insights, and next-step recommendations once the flight is complete.

If you live inside Ads Manager, understand lookalike modelling, and know how to squeeze every cent of value from Instagram inventory, let’s talk.

Skills: Internet Marketing, Google Adwords, Facebook Marketing, Ad Planning & Buying, Social Media Marketing, Conversion Rate Optimization, Digital Marketing, Data Analysis, Instagram Ads, Facebook Ads