Data Analysis Projects on Upwork Efficiently

Senior Statistical Modeler / Market Intelligence Data Scientist
Location
Contract Type
Contract (~6 months)
About the Role
We are seeking an experienced Statistical Modeler to support the design and implementation of a large-scale market intelligence and analytics platform. The role will focus on developing robust, transparent, and defensible estimation methodologies that combine multiple data sources to generate market size, market share, competitive intelligence, and business performance insights.
This is a highly applied role requiring a blend of statistical expertise, commercial analytics experience, and practical delivery skills. The ideal candidate will be comfortable working with imperfect real-world datasets, developing estimation frameworks, quantifying uncertainty, and communicating methodology to both technical and business stakeholders.
The successful candidate will work alongside data engineering, analytics, reporting, and business teams to build a scalable market intelligence capability supporting executive decision-making.

Key Responsibilities
Market Estimation & Statistical Modeling
• Design and implement market sizing and market share estimation methodologies.
• Develop coverage-adjusted projection models using partial or sampled data sources.
• Create weighting and expansion factor methodologies to project from observed data to total market estimates.
• Design stratified estimation approaches across channel, geography, retailer, product, and category dimensions.
• Develop confidence interval methodologies and uncertainty quantification frameworks.
• Build statistically defensible approaches for combining multiple independent data sources.
Data Integration & Triangulation
• Design methodologies for multi-source triangulation across internal and external datasets.
• Develop approaches for reconciling conflicting signals from different data providers.
• Establish statistical frameworks for data quality assessment and source reliability scoring.
• Support integration of panel data, scanner data, ecommerce data, syndicated data, and operational business data.
Validation & Model Governance
• Design backtesting frameworks to evaluate model performance.
• Define model accuracy metrics and monitoring approaches.
• Conduct sensitivity testing and scenario analysis.
• Create model stability assessments and drift monitoring processes.
• Document all assumptions, methodologies, calculations, and validation approaches.
Advanced Analytics
• Develop forecasting and predictive models where appropriate.
• Apply statistical and machine learning techniques to improve estimation accuracy.
• Evaluate advanced methodologies including Bayesian modeling, hierarchical models, ensemble approaches, and time-series forecasting.
• Recommend enhancements to improve confidence and reliability over time.
Stakeholder Engagement
• Explain methodology and results to non-technical stakeholders.
• Participate in workshops and methodology reviews.
• Present findings, assumptions, and limitations clearly.
• Support executive-level discussions regarding confidence, reliability, and interpretation of results.
Required Experience
Statistical Modeling
• 7+ years of hands-on statistical modeling experience.
• Strong background in applied statistics, econometrics, biostatistics, data science, quantitative analytics, or a related discipline.
• Demonstrated experience building estimation models from incomplete or sampled datasets.
• Experience calculating and interpreting confidence intervals, variance estimates, and uncertainty measures.
Commercial Analytics Experience
Experience in one or more of the following domains:
• Retail analytics
• Consumer packaged goods (CPG)
• Market measurement
• Market research
• Healthcare analytics
• Pharmaceutical analytics
• Consumer insights
• Ecommerce analytics
• Commercial forecasting
Statistical Techniques
Strong experience with several of the following:
• Sampling methodologies
• Weighting methodologies
• Expansion factor modeling
• Ratio estimation
• Stratified estimation
• Hierarchical modeling
• Bayesian statistics
• Confidence interval estimation
• Forecasting and time-series analysis
• Regression modeling
• Multivariate analysis
• Causal inference
• Sensitivity analysis
• Simulation techniques
• Monte Carlo methods
Technical Skills
Required:
• Python
• SQL
• Statistical modeling libraries
• Data analysis and visualization tools
Preferred:
• R
• Snowflake
• Databricks
• Power BI
• Tableau

We are a small SME (KMO) based in Belgium with 7 employees. Our company works in cable connections and utility infrastructure work for Fluvius.

The Excel files we need can be quite simple compared to more complex systems you may have built before. This is just a starting point for us, and I currently do not yet have the experience or time to work with very advanced or overly complicated systems.

At the moment, we are looking for basic but well-structured Excel workbooks to help us manage our company more efficiently. These should include:

Employee data management (personal and job details)
Company vehicles (registration, drivers, maintenance, etc.)
Insurance tracking
Training and certification tracking (this is very important for us)
Possibly other basic administrative follow-up sheets as we grow
.

For now, I am simply looking for clear, simple, and practical Excel solutions that are easy to use and maintain.

At this moment, this is everything that comes to mind, but the system may be expanded later as we gain more experience with it.

We are seeking a freelancer with expertise in bibliometric analysis using WoS/Scopus, VOSviewer, and Bibliometrix. The ideal candidate will not only produce graphs but also provide academic interpretation of the findings. This role requires a strong understanding of bibliometric tools and the ability to analyze data effectively. The project involves analyzing academic publications and providing insights into their impact and relevance.

Bibliometric Analysis Research Assistant Needed
I am preparing an academic article titled “Mapping the Evolution of Management Fashions in International Academic Literature: A Bibliometric Analysis of Web of Science Core Collection Articles, 2000–2025.”
I am looking for a researcher experienced in bibliometric analysis to support the data analysis section of the study. The expected tasks include:
Developing and refining the search strategy for Web of Science Core Collection
Exporting and cleaning bibliographic data
Conducting bibliometric analyses using VOSviewer and/or R Bibliometrix/Biblioshiny
Preparing co-occurrence, co-citation, bibliographic coupling, author/institution/country collaboration, and keyword evolution analyses
Producing publication-quality figures and tables
Preparing a methodological note explaining the data collection, cleaning, and analysis procedure
The topic is management fashions, management fads, institutional diffusion, and organizational studies.
Prior experience with WoS, Scopus, VOSviewer, Bibliometrix, and academic publication standards is required.
This is a paid research assistance task. Authorship or acknowledgement can be discussed depending on the level of intellectual contribution

I’m compiling a comprehensive spreadsheet of every active immigration pathway to Canada and need reliable, detail-oriented support. The assignment is straightforward—collect factual data, verify it on official Government of Canada sources, and input it into the Google Sheet template I’ll share.

Scope
• More than 20 distinct pathways must be covered, including federal, provincial, and pilot programs.
• For each pathway, I will provide the required information that I'll need but it includes: eligibility criteria, step-by-step application process, and required documents. I’ll provide a precise field-by-field checklist to keep the structure consistent.
• Source links must point to the exact government page where the information was taken.

Accuracy is critical. I will spot-check every row; any discrepancies will need immediate correction before the work is accepted. If a pathway is discontinued or merged into another stream, note that in the sheet rather than deleting it.

Deliverables
• Completed Google Sheet with all requested fields filled for every pathway
• Working source links for each data point
• Brief changelog noting any pathways you could not confirm on official sites and why

I expect clear, timely communication and daily progress updates so we can resolve questions quickly. If you are meticulous with data entry and comfortable navigating government immigration pages, this project should be a smooth fit.

Skills: Project Management, Data Entry, Research, Excel, Research Writing, Documentation, Data Analysis, Google Sheets, Data Collection, Data Management

I need a research assistant to help with analysis and interpretation in literary studies, specifically focusing on poetry. The ideal candidate should be tech-savvy and possess the following skills:

- Background in literary analysis, particularly in poetry or in coding thematic humanities data.
- Ability to use research tools and software efficiently (ATLAS.ti, QualCode).
- Experience in interpreting texts and providing feedback.
- Organized and able to manage research tasks effectively.

Please provide any examples you have of previous work in literary studies.

Skills: Research, Report Writing, Research Writing, Qualitative Research, Academic Writing, Data Analysis, Academic Research, Data Management

I am looking for a professional Telegram bulk DM service provider for a long-term partnership.

=== What I Have ===
- 290,000 phone numbers (country code +7)
- Customer data (phone)

=== What I Need ===
1. Send 1 promotional message to each number via Telegram DM
2. Message will contain a link to my Telegram channel
3. Provide detailed delivery report (delivered / failed / not on Telegram)
4. Ongoing monthly batches

=== Requirements ===
- MUST be able to send via phone number import (NOT just scraping from groups)
- Safe sending with anti-ban protection
- Daily sending capacity: at least 500-1000 DMs per day
- Delivery rate tracking and transparency

=== Budget & Payment ===
- Small test batch first: 100-500 DMs to verify quality
- Then scale up based on results
- Price: please quote per 1,000 DMs
- Payment via: Crypto (USDT) / Wise / PayPal

=== What to Include in Your Bid ===
1. Your price per 1,000 DMs
2. Estimated delivery rate (what % of messages actually reach inbox)
3. Your setup: how many accounts, proxy quality, anti-ban strategy
4. Do you provide delivery report? (Yes/No - with sample)
5. Any past experience with Russian phone number campaigns

=== Please Note ===
- If your approach is "scrape users from groups and DM them", this is NOT what I need.
- I already have the phone number list ready. I need someone who can import and send.

Looking for a reliable long-term partner. Serious bidders only.

Skills: Data Entry, Marketing, Social Media Marketing, Digital Marketing, API, Data Analysis, Lead Generation, Database Management, Data Management, Telegram API

Key Responsibilities
Market Research & Industry Analysis
Conduct comprehensive research on the Australian IML packaging market.
Identify major dairy, yogurt, cheese, butter, and ice cream manufacturers.
Analyze packaging trends, sustainability initiatives, and sourcing practices.
Evaluate existing packaging suppliers and competitive market dynamics.
Customer & Contact Development
Develop a database of target companies and key decision-makers.
Identify Procurement Managers, Packaging Managers, Purchasing Managers, Supply Chain Managers, and Innovation Teams.
Gather relevant business intelligence and market insights.
Business Development & Outreach
Represent Pooja Plastics in the Australian market.
Conduct outreach through LinkedIn, email, phone calls, and industry networks.
Introduce Pooja Plastics' IML packaging solutions and capabilities.
Generate qualified opportunities and arrange meetings with prospective customers.
Competitive Benchmarking
Analyze local packaging suppliers and compare their offerings with Pooja Plastics.
Identify areas where Pooja Plastics can offer competitive advantages in quality, sustainability, service, or cost.

Skills: Research, Sales, Marketing, Market Research, Database Development, Business Intelligence, Data Analysis, Business Development

PLEASE READ CAREFULLY!!

This is a quite simple/small classification project task especially for new comer in upwork and i need to complete this as soon as today,

I am looking for an experienced Machine Learning engineer to assist with a sentiment analysis/classification project. The primary model used in this study is XGBoost, trained on a dataset of approximately 1,500 labeled samples for online gambling (judol) detection. The objective is not only to build and evaluate the XGBoost model but also to conduct a comprehensive comparison with several other traditional machine learning algorithms to demonstrate the strengths and performance advantages of XGBoost.
The project should include a complete end-to-end workflow, starting from data preprocessing and exploratory data analysis (EDA), followed by feature engineering and model development. The comparison should be performed using appropriate baseline models such as Logistic Regression, Naive Bayes, Random Forest, Decision Tree, SVM, or other relevant algorithms. The final results should be presented in a clear

I expect a thorough evaluation using multiple performance metrics, including but not limited to Accuracy, Precision, Recall, F1-Score, ROC-AUC, and Confusion Matrix analysis where applicable. In addition, I would like comprehensive visualizations and plots, such as class distribution analysis, feature importance, correlation analysis (if relevant), confusion matrices, ROC curves, performance comparison charts, and any other insightful visual representations that strengthen the findings.
The deliverables should include well-documented and reproducible code, a clear explanation of the methodology, detailed interpretation of results, and professional quality visualizations. Experience with machine learning research projects, classification tasks, XGBoost optimization.
Please include examples of similar machine learning or data science projects you have completed in the past when submitting your proposal.

I’m looking for a freelancer who can consistently supply fresh, fully-verified individual consumer leads for our EdTech company. My focus is on people who actually make or influence enrolment decisions, so accuracy and intent are more important than sheer volume.

Target market
• Students
• Parents

What I need from you
- A repeatable strategy (organic or paid) that reaches the above two segments and converts them into qualified prospects.
- A lead file for each delivery containing, at minimum, full name, active email, phone (when available), location, and a short note on how the lead was captured or verified.
- Verification proof or tool report so I can see bounce-free emails and authentic numbers.
- Compliance with all relevant privacy regulations in the regions you plan to source from.

Acceptance criteria
The list must pass a random sampling test for contact validity (working numbers where provided) and must demonstrate genuine interest in online learning or skill development offers. Leads found to be duplicates, bots, or scraped without permission will not be counted.

If you already have access to proven data sources, enrichment tools (Hunter, Zerobounce, NeverBounce, Apollo, etc.), or past EdTech results, let me know—those will help me choose quickly. I’m ready to move fast and will provide feedback after the first batch so we can scale together.

Skills: Data Mining, Market Research, Email Marketing, Data Scraping, Data Analysis, Lead Generation, Data Collection, Data Management

We are a digital growth and performance agency looking for a reliable Data & BI partner to support one of our e-commerce clients on an ongoing basis.

This is not a fixed-scope role. Instead, we are looking for someone who can jump into projects as needed, investigate issues, provide estimates, and execute efficiently.

Typical Projects

* GA4 and GTM implementation, audits, and troubleshooting
* Tracking and attribution investigations
* Funnel.io configuration and support
* Looker Studio dashboard development and maintenance
* BigQuery analysis and data pipeline work
* Server-side tracking projects (Stape)
* Data discrepancies and reporting validation
* Marketing analytics support across Meta, Google Ads, Yahoo Japan, and Criteo

Client Stack

* Shopify
* GA4
* GTM
* Funnel.io
* Looker Studio
* BigQuery
* Meta Ads
* Google Ads
* Yahoo Japan
* Criteo

What We Are Looking For

* Strong hands-on experience with GA4, GTM, Funnel.io, Looker Studio, and BigQuery
* Ability to troubleshoot tracking and attribution issues independently
* Clear communication and documentation
* Ability to assess requests, estimate effort, and recommend solutions
* Comfortable working asynchronously through Slack

Engagement Model

Work will be assigned on a project-by-project basis. Some weeks may require only a few hours, while larger investigations or implementations may require more involvement.

When applying, please share:

* Relevant GA4 / GTM / Funnel.io experience
* Examples of Looker Studio or BigQuery projects
* Experience with server-side tracking (Stape or similar)
* Your hourly rate and availability

We are looking for a long-term partner rather than a one-off freelancer

Key Responsibilities
Market Research & Industry Analysis
Conduct comprehensive research on the Australian IML packaging market.
Identify major dairy, yogurt, cheese, butter, and ice cream manufacturers.
Analyze packaging trends, sustainability initiatives, and sourcing practices.
Evaluate existing packaging suppliers and competitive market dynamics.
Customer & Contact Development
Develop a database of target companies and key decision-makers.
Identify Procurement Managers, Packaging Managers, Purchasing Managers, Supply Chain Managers, and Innovation Teams.
Gather relevant business intelligence and market insights.
Business Development & Outreach
Represent Pooja Plastics in the Australian market.
Conduct outreach through LinkedIn, email, phone calls, and industry networks.
Introduce Pooja Plastics' IML packaging solutions and capabilities.
Generate qualified opportunities and arrange meetings with prospective customers.
Competitive Benchmarking
Analyze local packaging suppliers and compare their offerings with Pooja Plastics.
Identify areas where Pooja Plastics can offer competitive advantages in quality, sustainability, service, or cost.

Skills: Research, Sales, Marketing, Market Research, Database Development, Business Intelligence, Data Analysis, Business Development

Project Overview:

We are conducting a comprehensive assessment of an MRO (Maintenance, Repair & Operations) function and require an experienced analyst/consultant to support the analysis of workforce and operational data and develop executive-level insights and presentation materials.

The objective is to assess workforce structure, productivity, workload, capacity, operational efficiency, and workforce costs across multiple workshops and locations.

Available Data:

The selected consultant will be provided with Excel datasets containing:

• Workforce and employee data
• Workshop and location information
• Job card / work order data
• Productivity indicators
• Labor hours
• Salary and workforce cost data
• Overtime data
• Maintenance activities and service types

Scope of Work:

Workforce Assessment
• Actual workforce analysis
• Workforce distribution by workshop and region
• Productive vs non-productive workforce assessment
Capacity & Productivity Analysis
• Job cards per employee
• Workshop productivity analysis
• Workload distribution
• Capacity utilization assessment
Operational Analysis
• Service volume analysis
• Maintenance activity analysis
• Work order analysis
• Operational workload assessment
Turnaround Time Analysis
• Service completion time analysis
• TAT reporting by service type and workshop
Workforce Cost Analysis
• Salary cost analysis
• Overtime analysis
• Cost per employee
• Cost per workshop
Executive Reporting
• Develop executive-level PowerPoint presentation
• Create charts, dashboards, and management insights
• Identify key findings, risks, operational gaps, and recommendations

Required Experience:

• Workforce Analytics
• HR Analytics
• Operations Analytics
• MRO / Fleet Maintenance / Workshop Operations experience
• Advanced Excel (Pivot Tables, Power Query, Power Pivot)
• Power BI (preferred)
• Executive Presentation Development
• Data Storytelling

Deliverables:

• Clean analytical Excel workbook
• Executive PowerPoint presentation
• Key findings and recommendations
• Data gap assessment
• Executive summary

Please provide examples of similar workforce analytics, maintenance operations, fleet management, workshop optimization, or operational performance projects completed previously.

I need a skilled chemist to prepare a single 400 g batch of a Class 1 solid amine sorbent for tabletop carbon-capture tests. You will start by sourcing a high-surface-area mesoporous silica gel in the 150–250 µm range, then carry out a wet-impregnation loading with the amine you judge most suitable—branched PEI, TEPA, or a clearly justified alternative.

Once the loading is complete, dry the material fully so it ships free-flowing and ready for use. Before dispatch, characterise the sorbent’s specific CO₂ adsorption capacity and its cycling stability over repeated adsorption–desorption runs, then package the data in a concise report.

Deliverables
• 400 ± 5 g of dry, functional sorbent granules
• Laboratory report detailing: synthesis parameters, % amine loading, adsorption-capacity figure, cycling-stability curve, apparatus and test conditions
• Photos of the finished material and secure shipment to my address

Acceptance criteria
– Granule size within 150–250 µm range
– Reproducible CO₂ uptake and no >10 % capacity loss across stated cycles
– Clear documentation enabling future scale-up or repetition

Let me know your proposed amine choice, target loading percentage, and the testing setup you plan to use so we can lock the procedure before you begin.

Skills: Chemical Engineering, Documentation, Data Analysis, Research and Development

I am looking for a Filipino-based accountant who can step into our numbers, make sense of them, and turn everything into a clear, living forecast that the rest of the team—none of whom are accountants—can follow with confidence.

My main priority is financial planning, specifically budgeting. I need help building a brand-new budget from the ground up while also tightening the one we already use, so you will be working on both creation and optimisation. The end goal is a forward-looking model that lets us see where cash is headed each week, month, and quarter, and instantly spot where we must adjust.

I handle day-to-day operations, so I value plain-language explanations. Expect to translate accounting jargon into straightforward steps, annotate formulas, and highlight the levers that truly move our finances. You are free to choose the best tools—Excel, Google Sheets, maybe a lightweight dashboard—but the file must remain easy to maintain once you hand it over.

Deliverables
• A fully built, easy-to-edit budget and cash-flow forecast (spreadsheet or similar).
• A brief guide or loom-style walkthrough showing how each section works, where to update figures, and how to read the projections.
• Recommendations for keeping the model accurate as we scale (e.g., monthly checks, key ratios to watch).

Acceptance Criteria
• All calculations reconcile with our current statements.
• Anyone on the team can update core inputs without breaking formulas.
• Forecast reflects realistic scenarios and flags potential cash gaps at least 60 days out.

If this sounds like something you do in your sleep, let’s connect—I’m ready to get started right away.

Skills: Accounting, Excel, Financial Research, Finance, Financial Planning, Data Analysis, Google Sheets, Financial Modeling

I need several PDF files converted into clean, well-structured Excel workbooks. Every table in the PDFs contains text only—no numeric calculations—and the information is already laid out in table format. However, many rows and columns include merged cells that must be recreated accurately in Excel or otherwise handled so the data lines up perfectly when the sheet is filtered or sorted.

Your task is simple but precision-critical: extract all text, preserve the original column order, deal with merged-cell layouts, and deliver a fully editable .xlsx file for each PDF. Cell contents should match the source exactly (spelling, punctuation, line breaks) and no data should end up split, duplicated, or lost in the process.

Please use whatever method you prefer—manual entry, Power Query, Adobe, Python + pandas, or specialist OCR tools—as long as the output is 100 % faithful to the source tables and ready for immediate use.

Skills: Data Processing, Data Entry, Excel, PDF, Data Cleansing, Data Extraction, Data Analysis, Data Management

I’m building a clean, reliable database of suppliers that serve the retail industry and need thorough online research to make it happen. Your role is to identify legitimate retail-focused suppliers (not manufacturers or distributors) worldwide, verify their credibility, and capture three key data points for each one:

• Contact details (company name, address, website, phone, primary contact & email)
• Product offerings (concise description or catalogue link)
• Pricing details (public price lists, tiered pricing or the clearest indicative figures you can source)

Please return the information in a well-structured Excel or Google Sheet, with one row per supplier and separate columns for every required field. Links to original sources must be included so I can quickly validate the data.

Quality is more important than quantity; every entry should be recent, accurate and relevant to the retail sector. I’ll spot-check a sample before final acceptance, looking for working contact info, up-to-date product lines and pricing that matches what’s published on the supplier’s site or catalog.

If you’re comfortable with deep web research, data verification and clear spreadsheet organisation, I look forward to reviewing your proposal and timeline.

Skills: Data Entry, Research, Excel, Web Search, Data Analysis, Google Sheets, Database Management, Data Collection

I have several spreadsheets and database exports that need to be merged into one clean, well-structured Microsoft Excel file. The records contain both text and numbers—customer names, product IDs, quantities, dates, and similar fields—so every entry has to be transferred with absolute accuracy.

Your task is to:
• Consolidate all sources into a single .xlsx workbook, arranging columns consistently.
• Preserve original values and number formats while removing obvious duplicates, extra spaces, and stray characters.
• Apply appropriate Excel formatting for dates, currency, and percentages so the data is ready for analysis.
• Provide a short change log noting any anomalies or assumptions.

If you are detail-oriented, fast, and comfortable working exclusively in Excel, I look forward to seeing how quickly you can complete this.

Skills: Data Processing, Data Entry, Excel, Word, Data Cleansing, Data Analysis, Database Management, Data Management

Saya sedang menyelesaikan tugas penelitian untuk mata kuliah Ilmu Sosial dan membutuhkan pendampingan menyeluruh dengan pendekatan studi kasus.
Lingkup kerja yang saya harapkan meliputi:
• Penyusunan kerangka teori yang relevan dan mutakhir.
• Perumusan pertanyaan penelitian spesifik untuk studi kasus.
• Desain metodologi studi kasus—mulai dari penentuan subjek, instrumen pengumpulan data, hingga rencana analisis.
• Panduan pengumpulan data lapangan atau desk research, beserta contoh instrumen wawancara/observasi jika diperlukan.
• Bantuan analisis data kualitatif dan interpretasi temuan agar selaras dengan tujuan penelitian.
• Penyusunan laporan akhir yang mencakup pendahuluan, tinjauan pustaka ringkas, metodologi, hasil, diskusi, dan kesimpulan.

Saya terbuka berdiskusi mengenai tema kasus spesifik, format sitasi, dan batasan panjang tulisan. Mohon sertakan pengalaman Anda di bidang penelitian Ilmu Sosial, contoh studi kasus yang pernah ditangani, serta perkiraan jadwal penyelesaian. Saya menargetkan hasil yang rapi, terstruktur, dan siap dikumpulkan sesuai standar akademik.

Skills: Data Processing, Data Entry, Research, Excel, Web Search, Qualitative Research, Academic Writing, Data Analysis

I have a collection of digital files—mainly PDFs and Word documents—that need to be transcribed with care into structured Excel spreadsheets. Everything must be entered manually rather than through any automated scraping or conversion tools, so close attention to spelling, punctuation, and cell formatting is essential.

You will receive the source files, and I will provide a simple template that shows the required column order, data types, and any validation rules. Once the first few rows are complete, we can do a quick review together to confirm the layout before you proceed with the remaining records.

Deliverable:
• One fully-populated Excel workbook matching the template, ready for immediate use.

Accuracy and consistency matter more than speed; however, a clear turnaround estimate helps me plan the next stage of the project. Let me know your availability and how soon you can start.

Skills: Data Processing, Data Entry, Excel, Transcription, Word, Word Processing, Data Analysis, Data Management

Saya membutuhkan bantuan untuk dua hal sekaligus: merapikan dokumen melalui pengetikan ulang yang rapi, lalu menganalisis data untuk menghasilkan laporan yang mudah dipahami. Dokumen sumber sudah tersedia dalam berbagai format (PDF, gambar, dan lembar kerja mentah); saya ingin semuanya diketik ulang atau di-input ke Excel/Google Sheets agar siap diproses lebih lanjut.

Setelah data tersusun, saya memerlukan:
• pembersihan data dasar (penghapusan duplikat, koreksi format angka/tanggal)
• analisis statistik ringkas dan visual sederhana (tabel pivot, grafik tren, atau diagram batang—pilih metode paling relevan)
• ringkasan temuan utama dalam satu laporan singkat (boleh di Word atau PowerPoint)

Kunci keberhasilan proyek: akurasi pengetikan, konsistensi format, serta kemampuan menyajikan insight yang jelas dari data mentah. Jika Anda memiliki pengalaman melakukan dua jenis tugas ini secara bersamaan, jelaskan secara singkat di lamaran Anda—saya memprioritaskan freelancer dengan rekam jejak serupa.

Berikan estimasi waktu penyelesaian untuk:
1. proses pengetikan/input, dan
2. pembuatan analisis beserta laporan.

File contoh akan saya kirim setelah kita sepakat. Saya menantikan kolaborasi yang lancar dan hasil yang tepat sasaran.

Skills: Data Processing, Data Entry, Excel, Word, Statistical Analysis, Data Cleansing, Data Visualization, Data Analysis

I need a clear, data-driven picture of Iraq’s automotive market so I can decide how and where to enter the country. This is strictly a market research assignment, focused on passenger and light-commercial vehicles rather than heavy machinery.

What I expect you to uncover
• Current size and value of the market, broken down by new versus used imports
• Growth trajectory over the past five years and any signals about the next three
• Key brands and distributors, their estimated share, and how they position themselves
• Regulatory environment—import duties, taxes, fuel subsidies, financing rules, and registration processes that affect pricing and demand
• Typical consumer purchase drivers (price sensitivity, after-sales service, brand perception, availability of parts) drawn from reliable primary or secondary sources
• Distribution and retail landscape: dealer networks, informal channels, and emerging online platforms
• Practical opportunities and risks for a new entrant

Research approach
Leverage a mix of publicly available statistics, trade publications, dealer or industry interviews, and on-the-ground observations. Arabic and Kurdish language sources should be tapped wherever useful; English summaries are fine for inclusion in the final report.

Deliverables
1. A concise PDF report (15-25 pages) synthesising insights, charts, and actionable recommendations
2. An Excel or Google Sheets file with all raw data, source citations, and calculations
3. A short slide deck (10–12 slides) I can share with stakeholders

Acceptance criteria
• All figures are traceable to cited sources dated within the last three years
• Assumptions are clearly stated; no unsupported extrapolations
• Visuals (graphs, tables, maps) are easy to read and editable

I welcome your proposed timeline, brief outline, and any clarifying questions before we start.

Skills: Research, Financial Research, Business Analysis, Market Research, Statistical Analysis, Data Analysis, Market Sizing, Market Analysis

I have several spreadsheets that need to be updated quickly and accurately. All source material is in plain text, and your job is to transfer that text into the correct columns, then reconcile it with the information already in the file so everything lines up perfectly.

You will be working in Excel (or Google Sheets if you prefer) and matching each new entry against existing rows to catch duplicates, spot missing values, and keep totals consistent. Accuracy matters more than speed, but I would like steady progress with regular check-ins so we can correct issues early.

Deliverables
• Clean, fully populated spreadsheet with all plain-text data copied into the right fields
• Reconciled data set: no duplicates, balanced figures, and clear flags on any anomalies you uncovered
• Brief summary of issues found and the actions you took to resolve them

If you are meticulous with spreadsheets and comfortable doing straightforward copy-paste work that requires a sharp eye for discrepancies, I’d like to get started right away.

Skills: Data Processing, Data Entry, Excel, Word, Data Analysis, Data Integration, Google Sheets, Data Management

I have six to ten PDF files filled with neatly structured tables that must be recreated in Excel. Every value, symbol, row, and column needs to appear exactly as in the originals so the final workbook mirrors the source documents without a single discrepancy.

Accuracy is non-negotiable, so please lean on Adobe Acrobat, reliable PDF-to-Excel utilities, and precise OCR techniques to prevent misreads. Before tackling the full batch, share a short sample from the first file so we can confirm layout and formatting.

Deliverables
• Excel workbook(s) that replicate each table perfectly
• No data loss—figures in Excel must reconcile with the PDFs
• Confirmed sample prior to full submission

Once the sample is approved, a swift turnaround on the remaining files will keep the project on schedule. Let me know if any detail needs clarification.

Skills: Data Processing, Data Entry, Excel, OCR, Excel Macros, Data Analysis, Adobe Acrobat, Data Management

We are seeking a Data Governance Architect or Product Manager to support the development of a practical data governance framework and help accelerate key data quality and business lineage initiatives. This role is ideal for someone who can step into a complex environment, quickly understand stakeholder needs, synthesize large amounts of input, and turn ambiguity into clear requirements, recommendations, and execution plans.

The ideal candidate will bring a consulting mindset, strong product management discipline, and hands-on experience with data governance concepts. This person will help analyze stakeholder transcripts, meeting notes, discovery feedback, and existing documentation to identify common themes, business pain points, process gaps, and opportunities for improvement.

Responsibilities include supporting the definition of governance policies and standards, documenting business and technical requirements, helping prioritize data quality use cases, and contributing to a clear game plan for business lineage. The role will work closely with governance leaders, business stakeholders, product teams, and technology partners to organize inputs, clarify scope, and translate findings into actionable recommendations.

This is a high-impact support role for an experienced Data Governance Architect or Product Manager who can bring structure, independent analysis, and practical execution support to a growing governance program. The focus is on helping the organization make better decisions, align stakeholders, and move data quality and lineage work forward with greater clarity and confidence.

I need a hands-on data scientist to turn a set of time-stamped records into a working regression model that can reliably forecast future values. The project’s primary objective is to develop a predictive model—specifically, a regression solution built on time series data.

Here is what I will provide:
• A cleaned, well-structured dataset (CSV) that includes the historical target variable and supporting features.
• A short brief on the business context and the key performance metric I care about.

What I expect from you:
• Exploratory analysis that highlights trends, seasonality, outliers, and any useful lags or engineered features.
• A robust regression model suited to time-series behaviour (ARIMA, Prophet, XGBoost, LSTM, or similar—feel free to justify the best choice).
• Code written in Python using familiar libraries such as Pandas, NumPy, Scikit-learn (plus statsmodels, TensorFlow, or PyTorch if needed).
• Clear evaluation with train/validation splits, back-testing, and accuracy metrics (MAPE, RMSE, or another metric we agree on).
• Concise visualisations—matplotlib / seaborn for the notebook and, if helpful, a lightweight Power BI or Jupyter dashboard so stakeholders see how the predictions track actuals.
• A brief report or notebook markdown explaining assumptions, feature engineering steps, model interpretation, and how the results translate into actionable insights.

Deliverables will be:
1. The complete, reproducible Python code (notebook or .py).
2. Saved model artefacts ready for deployment.
3. Visual output illustrating forecast versus actual performance.
4. A short hand-off document so the business team can rerun or extend the work.

If this scope matches your expertise in Python, SQL, machine learning, statistics, and data visualisation, let’s get started—I’m ready to move quickly once we align on approach and timeline.

Skills: Python, Statistics, Statistical Analysis, Data Science, Data Visualization, Data Analysis, Time Series Analysis

I run a residential-and-commercial cleaning company in Sydney and I want to take our marketing stack to the next level. The goal is full campaign automation, from data flowing out of GoHighLevel to fresh ads going live and budgets being tuned without constant hand-holding.

Here’s what I need you to set up:

• Connect GoHighLevel with both Meta Ads Manager and Google Ads through API or webhooks so every new lead, tag change, or appointment instantly syncs to the ad platforms.
• Layer Claude AI on top of that connection. Claude should pull performance data, generate new creative variations, adjust bids, and push approved changes live—covering data analysis, ad creation, and bidding/budget management end-to-end.
• Build new GHL workflows: lead capture to booking confirmation, follow-up email and SMS sequences, reactivation campaigns, and referral prompts—all tailored for a Sydney cleaning audience.

Primary objective: automate campaign management. We currently lean on social media campaigns, so the integrations must keep Facebook/Instagram performance tight while expanding to Google.

Acceptance criteria
1. Data from GHL (lead details, stage changes) appears in both ad dashboards within minutes.
2. Claude AI successfully generates at least two new ad sets per week, with bid adjustments logged and visible.
3. New email/SMS automations trigger correctly in test mode, include merge tags, and track opens, clicks, and bookings.

If you’ve connected GoHighLevel to ad platforms before and are comfortable orchestrating AI tools like Claude, let’s talk. I’m ready to provide account access and jump straight into implementation.

Skills: PHP, Website Design, Software Architecture, HTML, Digital Marketing, API, AI Development, Claude (Anthropic), GoHighLevel

I have several spreadsheets that need to be updated quickly and accurately. All source material is in plain text, and your job is to transfer that text into the correct columns, then reconcile it with the information already in the file so everything lines up perfectly.

You will be working in Excel (or Google Sheets if you prefer) and matching each new entry against existing rows to catch duplicates, spot missing values, and keep totals consistent. Accuracy matters more than speed, but I would like steady progress with regular check-ins so we can correct issues early.

Deliverables
• Clean, fully populated spreadsheet with all plain-text data copied into the right fields
• Reconciled data set: no duplicates, balanced figures, and clear flags on any anomalies you uncovered
• Brief summary of issues found and the actions you took to resolve them

If you are meticulous with spreadsheets and comfortable doing straightforward copy-paste work that requires a sharp eye for discrepancies, I’d like to get started right away.

Skills: Data Processing, Data Entry, Excel, Word, Data Analysis, Data Integration, Google Sheets, Data Management

I have 2 potential investment opportunities that requested a loan. I need to know if the loan is covered based on the phases of construction and the true fair price at completion.
Basically, do we fund the construction projects or not. All the necessary information will be given to you to once we establish some rapport. Including but not limited to budget, pro-forma, collateral, cap rates, P&L statements and property information etc…

I will then possibly have you explain it to me in detail, I simply want for us to collaborate our investment thesis together to find errors in my approach.

Some are construction projects others are fully stabilized assets.

One of the more memorable projects I have worked on recently was a Kaggle competition centered around stellar classification.

The goal was straightforward: classify celestial objects into three categories, there are galaxies, stars, and quasars using photometric data from the Sloan Digital Sky Survey (SDSS). Simple in concept, but the execution required quite a bit of thought.

Here is what I focused on throughout the project:
Feature Engineering
I built over 60 new features from the original SDSS bands (u, g, r, i, z). These included colour differences between bands, flux ratios, energy distribution patterns, and redshift-based combinations. Out of everything I tested, redshift turned out to be the most useful variable for telling the three object types apart.
Ensemble Modeling
I trained three models, LightGBM, XGBoost, and CatBoost each models using 10-fold stratified cross-validation. Once I had a clear picture of how each model performed, I merged their predictions through weighted blending and added a stacking layer on top to squeeze out a bit more accuracy.
Prediction Optimization
Since the competition scored entries using balanced accuracy, I could not just rely on raw model outputs. I worked on adjusting the decision weights for each class, which helped the model handle class imbalance better and pushed the final score higher than I expected.
Current result: 96.68% Balanced Accuracy

A few things I took away from this experience:
- Good feature engineering still matters a lot, even when the models themselves are already strong.
- Post-training steps like calibration and threshold adjustment can move the needle more than people often expect.
- Blending multiple models together tends to give more reliable results than betting everything on one.

Source code available here: https://lnkd.in/gUFZZ6sv

If you are currently working on a Kaggle competition or a machine learning project, feel free to reach out, I am always up for a good conversation about this stuff.

Skills: Machine Learning (ML), Data Mining, Statistical Analysis, Data Science, Data Visualization, Data Analysis, Deep Learning, AI Model Development, AI Research, AI Development

I’ve collected a sizable housing-market dataset and now need a complete prediction pipeline built in Python. The work starts with thorough cleaning, preprocessing, and creative feature engineering so that every useful signal—size, rooms, location ratings, and any other attributes we can derive—is captured.

Once the dataset is ready, I want to benchmark several approaches, but the core focus is Random Forest Regression. Feel free to test Linear or Support Vector methods if they might edge out the forest, yet the final report should clearly show how each model performs against the usual metrics (RMSE, MAE, R²).

Visual insight is important, so the notebook or script has to generate intuitive plots—scatter trends, residual diagnostics, whatever best tells the story of model quality and feature impact. After modelling, package the chosen estimator in a lightweight Streamlit app where a user can key in property details and instantly see a predicted price.

Deliverables
• Clean, well-commented Python code (Pandas, NumPy, scikit-learn, Matplotlib / Seaborn, Streamlit)
• A concise report explaining preprocessing steps, feature choices, model comparison results, and recommendations
• The Streamlit interface ready to run locally (with instructions)
• Any supplementary documentation needed to reproduce the full workflow end to end

If something in the data suggests additional techniques—hyper-parameter tuning, cross-validation strategies, or advanced visualisations—please flag it and incorporate where it boosts accuracy or interpretability. I look forward to your expertise turning raw rows into a reliable, user-friendly pricing tool.

Skills: Python, Statistics, Machine Learning (ML), R Programming Language, Statistical Analysis, Data Science, NumPy, Data Visualization, Data Analysis, Pandas

I have a full-disk .img taken from a Linux server and I need the usable information pulled out of it. The goal is to mount the image, navigate its file system, and recover only the files and directories that hold application data, with particular attention to the database stores.

If any corruption is encountered, let me know the options before attempting repairs so we do not risk further damage.

Deliverables
• A compressed archive containing the recovered database directories and any essential config that keeps them functional
• A concise log of the commands or steps you used so I can reproduce the process if needed

All file permissions, ownership, and timestamps must remain intact, and the original image must never be altered during the operation. If this is straightforward for you, let me know how soon you can begin and an estimated timeframe for completion.

Skills: Linux, Data Processing, Data Extraction, Data Analysis, Database Management, Data Management, Data Backup, System Administration