Discover Data Mining Projects on Upwork

We have a list of Etsy store URLs and need someone to find the owners’ email addresses.

Requirements:

* Find the email for each store owner
* Validate every email before delivery
* Deliver only verified emails

When applying, please include:

* Your experience
* The tools you use
* Your price per 1,000 validated emails
* Estimated turnaround time

Resolved AI lead filtering issues where leads were not being classified correctly.
Debugged and fixed AWS-related issues affecting automation workflows and backend services.
Improved API integrations, workflow reliability, and overall system performance.
Monitored logs, identified root causes, and implemented fixes to ensure stable AI automation.

We are seeking an AI-Powered Lead Generation Expert to enhance our B2B lead generation process. The role involves utilizing AI tools to identify and verify potential leads, enrich data, and ensure accuracy in email verification. The ideal candidate will have experience in managing lead generation campaigns and optimizing processes for better results.

We are seeking a high-level CRM expert to manage leads and client outreach. The ideal candidate will have extensive experience with CRM systems and a proven track record in lead management. Responsibilities include developing and implementing effective lead management strategies, enhancing client outreach processes, and optimizing CRM systems for maximum efficiency. The role requires strong analytical skills and the ability to work independently.

I need a real-time data pipeline that ingests tick-by-tick football information from the Betfair API for each match taking place in the top five European leagues (Premier League, La Liga, Serie A, Bundesliga, Ligue 1). The feed must rely exclusively on this API—no scraping—so skill with Betfair’s Streaming or Historical service is essential.

The stream should enrich every tick with contextual match metadata and persist it in an easily queryable store (PostgreSQL, parquet on S3, or a solution you propose). Low-latency processing is critical; sub-second lag from the API to storage is my target. I plan to run the pipeline on AWS, so please factor in services such as Kinesis, Lambda, Fargate or similar if they fit the design.

Deliverables
• Codebase (Python preferred) that connects to Betfair’s live odds stream and continuously captures:
 – Match ID, date, league, home & away teams
 – Current match minute / exact timestamp of each tick
 – Current live score (home goals, away goals)
 – Red card status when available
 – Exact live 1X2 odds at that moment
• Automated process to write these ticks to the agreed storage layer in near-real time
• Schema documentation and setup instructions (environment variables, API keys, AWS IAM roles, etc.)
• Sample analytics notebook that demonstrates pulling a match and plotting odds movement versus scoreline

Acceptance criteria
• End-to-end test on an active match shows all required fields emitted within one second of the API update
• Historical replay of a completed match accurately reconstructs every odds change and score event
• Code passes linting and includes unit tests for core functions

Let me know which AWS services or alternative stack you would choose, any rate-limit considerations with Betfair, and an estimated turnaround.

Skills: Data Processing, Data Mining, Database Development, Data Visualization, Data Analysis, Data Integration, Database Management, Data Collection, Data Management, Big Data

Requirements:
Previous experience finding police bodycam footage.

Experience sourcing interrogation videos, mugshots, arrest reports, 911 calls, and other publicly available law enforcement records where legally available.

Ability to research and obtain original footage through the proper public records process.
Must know how to find high-quality, viral-worthy cases.

Must provide proof of previous work (portfolio, screenshots, examples, or references).
DO NOT APPLY if you have no previous experience with police bodycam or FOIA/public records research. We are only looking for someone who has done this type of work before.
When applying, include:

Examples of previous bodycam research projects.

Proof of successful footage sourcing.

A brief explanation of your experience and workflow.

DO NOT Apply if you dont understand what footage to get, no random data just specific footage that the viewers watch.

• What different channels have u worked with. Do you understand what data to get, the most interesting case and not just get random data-footage

We are building a Central Data Hub on ArcGIS Online for a climate change and disaster resilience programme, and are looking for an expert who can act as both technical advisor and implementer — first reviewing our preparation and telling us what's really needed, then delivering the platform.

The work: ArcGIS Online org foundation and master domains · ArcGIS Hub site (~8 thematic categories) · migration of six survey instruments from KoboToolbox (XLSForm) to Survey123 · secure/public hosted-view architecture for sensitive data · a packaged, re-runnable ETL toolkit (ArcGIS API for Python) our staff will operate · dashboards, documentation and remote training. This is an unusually well-prepared project — dataset inventory, target schemas, data dictionary and governance design already exist, and a single coordinator handles all liaison with data owners. The attached PDF has the full role description, deliverables and skill requirements — please read it before applying.

Key terms:

You will never access sensitive or personal data. Development is against empty forms, synthetic data and de-identified samples; our staff run the real loads with your tools. Apply only if comfortable with this model.

Fixed-price milestones with written acceptance criteria. Bid your price per milestone — total capped at US$7,150 (trial fixed at $400, support retainer fixed at $250/month × 3). Quality and work samples outrank price.

We start with a paid US$400 trial task (one XLSForm adapted and published to staging, one scripted append of synthetic rows, QA report), possibly run with two candidates — both paid.
Shortlisted candidates get a video call, sign a simple NDA, then receive full project context.
~100–140 hours over 2–3 months, part-time. Good overlap with UTC+12 working hours preferred.

To apply: see the Full Job Description attached.

Need a Web Scraper to give me a list of all tech sales recruiters emails

We are seeking a detail-oriented and reliable Data Entry Clerk to join our team. The ideal candidate will be responsible for accurately entering, updating, and maintaining data in company databases and systems. This role requires strong organizational skills, attention to detail, and the ability to work efficiently while maintaining a high level of accuracy.

Key Responsibilities
Enter, update, and verify data in company databases and systems.
Review source documents for accuracy and completeness before data entry.
Correct errors and maintain data integrity.
Organize and maintain digital and physical records.
Generate reports and retrieve data as requested.
Ensure confidentiality and security of sensitive information.
Collaborate with team members to resolve data discrepancies.
Meet daily, weekly, and monthly productivity targets.
Perform other administrative tasks as assigned.

I am looking for an experienced Python developer to build a Windows desktop automation tool.

The tool should automatically process digital bank statement PDFs (text-based, not scanned) and extract all transactions into a predefined Excel format.

This is not a simple PDF-to-Excel converter. I need a tool that understands the structure of bank statements, accurately parses every transaction, and places each value into the correct Excel column.

Each transaction must appear as a separate row in the Excel file.

The Excel output must contain the following columns in Hebrew (please keep the column headers in Hebrew):

Hebrew Column English Meaning
יום Day
סוף End of Day
מקור Source
תאור פעולה Transaction Description
אסמכתא Reference Number
צרור Batch
ערך Value Date
תנועה Transaction Amount
יתרה Balance
זמן- Time
נגדי: חשבון- Counterparty Account
סניף- Branch
בנק- Bank
המבצע- Performed By
עבור- For
מספר עמוד- Page Number
Project Requirements
The PDF files come from multiple banks.
Each bank has its own consistent PDF layout.
The application should be designed so that support for additional bank formats can be added in the future.
The tool must automatically detect every transaction.
Every extracted value must be placed in the correct Excel column.
Accuracy is the highest priority.
Missing transactions, duplicated transactions, or incorrectly mapped values are not acceptable.
If the parser is uncertain about a transaction or a specific field, it should flag it for review instead of generating incorrect data.
The application must run locally on Windows.
I need the complete Python source code.
I will provide
Sample PDF bank statements.
An Excel template showing the required output format.
Additional PDF samples if needed.
Goal

The goal is to achieve the highest possible extraction accuracy (ideally above 99%), even if that requires building custom parsers for each bank's PDF format. Reliability and accuracy are much more important than development speed.

Note: The budget entered in the contract is only a placeholder because Upwork required a value.

Please do not consider it as my actual budget.

First, I would like to know whether this project is relevant to your expertise and whether you would be interested in building such a tool.

If so, I can provide sample PDF files and the required Excel format. After reviewing them, I would appreciate it if you could provide an approximate fixed-price quote and an estimated development timeline.

I'm looking to hire someone for a lead generation project. I need accurate and verified leads based on my target industry.
Required:
Company name and website
Contact person
Verified email
Location
LinkedIn profile

I am working to build a database of Family Office investors. I have attached a file here that includes close to 250 potential family offices. Can you help me pull two or three contacts at each firm? I added a column to the far right with ideal titles for each firm. I also have another tab in there called Monarch Contacts where we do have email addresses and contacts for at least one person from some of these organizations. you can use that to help confirm email address format where possible. Thank you!

Hi Sachin! I am looking for a reliable, long-term sourcing and fulfillment partner based in India for an e-commerce store operating in Latin America.
Your main responsibilities will be:
Sourcing the Be Bodywise Hair Growth Serum Roll-on (25ml) locally at the best possible price (ensuring 100% original product).
Storing a small batch of inventory at your location.
Fulfilling individual orders and shipping them to Colombia (South America) using a trackable and economic shipping method (like India Post Registered Airmail, DHL eCommerce, or FedEx).
Please let me know:

Your estimated fee per package/fulfilled order or your hourly rate for this workflow.
The average shipping cost to Colombia for a package under 100g.
Estimated delivery times.

I need a system to scrape Depop and Vinted for price gaps to resell on platforms like Depop, eBay, or Poshmark. The system should compare buy-low/sell-higher country price gaps, allowing me to identify profitable resale opportunities. The ideal candidate will have experience in web scraping and data analysis to effectively gather and interpret data from these platforms.

• Describe your recent experience with similar projects
• Describe your approach to testing and improving QA

MARKET DATA RESEARCHER & SPREADSHEET BUILDER
Home-services launch data pull — Washington DC + Fredericksburg VA

Type: Fixed-price, milestone-based
Estimated effort: 25–40 hours
Level: Intermediate–Expert
Skills: Census/ACS data, data extraction & cleaning, Google Sheets/Excel, Google Keyword Planner, public-records research

TO APPLY: Start your proposal with the word "PIPES" so we know you read the full post.

—————————————————————————

WHAT WE'RE BUILDING
We're a pre-launch home-services startup that matches homeowners to vetted plumbing, HVAC, and electrical contractors. Before we spend a dollar on marketing, we need clean data to drive two decisions: (1) which ZIP areas we market in first, and (2) which single trade — HVAC, plumbing, or electrical — we launch with.

This is a well-defined, follow-the-spec build, not open-ended research. We've already identified every source and the exact tables. We need someone precise to pull, clean, and organize it into the spreadsheet described below. Accuracy and clear sourcing matter more than speed.

THE RULES THAT MATTER MOST
- Every number must trace to a source — URL, exact table/dataset name, and date pulled, logged in the workbook.
- Never fabricate or "fill in" a number. A blank, flagged cell is always better than a guess.
- Label estimates and benchmarks clearly vs. hard local figures.
- Use formulas, not hard-coded values, for anything calculated.

OUT OF SCOPE
Do NOT include market-size or industry-report research (e.g. IBISWorld, Statista, TAM sizing). It is not part of this project. Everything you need is the free public data below plus the one Semrush account we provide.

GEOGRAPHIES (EXACT)
- DC: all Washington DC ZIP codes / ZCTAs (~68).
- Fredericksburg core: 22401, 22405, 22406, 22407, 22408.
- Border ZIPs (separate tab): Stafford 22554, 22556; Spotsylvania 22553, 22551.

—————————————————————————

DELIVERABLE: ONE GOOGLE SHEETS WORKBOOK (7 TABS) + A SHORT SOURCES DOC
Share edit access. Every tab: frozen header row, one row per ZIP/item, a "Source & Date" column, numbers formatted as numbers.

TAB 1 — ZIP_Master (core data, one row per ZIP)
Pull the most recent ACS 5-Year data by ZCTA from data.census.gov for every ZIP above. Fields and their ACS tables:
- Total occupied units; owner-occupied # and %; renter % — table B25003
- Units in structure: 1-detached, 1-attached (rowhouse), 2–4, 5–19, 20-plus (# and %) — table B25024
- Year built: pre-1940, pre-1960, pre-1980, 2000–2019 (# and %) — table B25034
- Median home value — table B25077
- Median household income — table B19013
- Heating fuel mix (gas / electric / oil %) — table B25040
Bonus if available: B25127 (tenure by year built by structure) for an "owner-occupied + old + single-family" count per ZIP.

TAB 2 — ZIP_Score (weighted ranking)
Pull values from Tab 1 and compute a 0–100 score per ZIP. Put the weights in editable cells at the top so we can tune them. Normalize each metric 0–100 across the set (min-max), multiply by weight, sum. Rank best to worst with a color scale, and add filter views for "DC only" and "Fredericksburg only." Weights:
- Owner-occupancy rate — 25% (higher is better)
- Single-family + rowhouse share — 20% (higher is better)
- Pre-1980 housing share — 20% (higher is better)
- Median home value / income, blended — 15% (higher is better)
- CAC / competition (from Tab 6, inverse) — 15% (lower cost is better)
- Contractor coverage (from Tab 4) — 5% (higher is better)

TAB 3 — Permits_Demand (per-trade demand by ZIP)
Trailing-12-month permit counts by ZIP, split into Electrical / Plumbing / Mechanical(HVAC), plus a total.
- DC: opendata.dc.gov "Building Permits 2025/2026" (includes electrical/plumbing/mechanical supplemental permits with addresses — aggregate to ZIP).
- VA: permits.virginia.gov plus Fredericksburg City / Stafford / Spotsylvania portals. If a locality can't be pulled, note it and flag the gap — don't guess.
Add a note that permits skew toward major/replacement work, not small repairs.

TAB 4 — Contractor_Supply (supply by trade & market)
4a. Virginia (DPOR Regulant Lists — free .txt downloads at dpor.virginia.gov/RegulantLists): one row per active licensee — license #, name/firm, trade code (MELE/JELE electrician, MPLB/JPLB plumber, MHVA/JHVA HVAC, MGFC/JGFC gas fitter), class (A/B/C/Tradesman), city, ZIP, expiration, active? (expiration date is today or later). Then a summary: active count by trade within (i) the Fredericksburg/Stafford/Spotsylvania ZIPs and (ii) a ~45-minute radius.
4b. DC — MUST be done manually. DC has no bulk download. You are required to query the OPLA license search directly (govservices.dcra.dc.gov/oplaportal) and tally counts by trade (Electrician / Plumber-Gasfitter / Refrigeration & A/C) by hand. Do NOT substitute a records request, an emailed data request, or a third-party/scraped dataset — the DC figures must come from your own manual search of the portal. Document your method and any limits.

TAB 5 — Trade_Economics (the wedge sheet: HVAC vs Plumbing vs Electrical)
One row per trade: average repair/service ticket (national + DC/VA note), typical repair range, average replacement ticket, emergency-call urgency, seasonality (variance %), DC onboarding burden, VA onboarding burden, supply depth (link Tab 4), Source & Date. Pre-fill and cite these verified onboarding facts:
- Electrical: DC accepts MD/VA electricians by reciprocity (no DC exam) — easiest onboarding, biggest pool.
- HVAC (Refrig & A/C): no DC reciprocity — standalone DC license required — hardest cross-border onboarding.
- Plumbing/Gasfitting: no broad DC reciprocity, but a WSSC exam agreement eases MD/VA suburban plumbing/gas.
- DC Home Improvement Contractors: $25,000 surety bond + criminal-history check; note the "no advance payment unless bonded" rule.

TAB 6 — CAC_Marketing (validate acquisition cost)
6a. Live local pull — Google Keyword Planner (free Google Ads account): for a keyword set we'll provide (e.g. "emergency plumber," "AC repair near me," "electrician near me," "water heater repair," "furnace repair," "panel upgrade"), pull local monthly search volume + top-of-page CPC (low/high) + competition, filtered to (i) DC and (ii) Fredericksburg. Key output: is DC's CPC materially higher than Fredericksburg's?
6b. Sharper local volume/competition — Semrush (account provided; login shared privately after award). Use it to pull exact local monthly search volume, keyword competitive density, and competitor-PPC intelligence (who is bidding on these terms) by trade and metro — the detail Keyword Planner buckets too coarsely.
6c. Benchmarks (free/published): a small table of CPL & cost-per-customer by trade and channel — Google LSA CPL, non-branded search CPL, LSA cost-per-paying-customer, Angi/Thumbtack shared-lead range — each with source.
6d. Meta note (not a full pull): from the free Meta Ads Library, count active local HVAC/plumbing/electrical advertisers per market as a density signal, and list a benchmark Meta CPM/CPC range with source. One line on why Meta is a secondary/retargeting channel for emergency repair, not primary.
6e. CAC scenario block: job value (default $550) x 23% = gross take, then contribution at CAC = $18 / $40 / $80 / $150, so we can see where unit economics break.

TAB 7 — Sources_Log
Every source: name, URL, exact dataset/table, date pulled, free/paid, and any limitation notes. Mirror this in a short companion Google Doc ("Sources & Method").

—————————————————————————

PAID TOOL — WE PROVIDE THE ACCOUNT (SEMRUSH)
There is one paid source for this job: Semrush. We provide the account — you do NOT need your own subscription, and do not purchase anything. We'll share the Semrush login privately through Upwork Messages once we award the contract, not in this public post.

MILESTONES
1. Milestone 1: Tab 1 (ZIP_Master) + Tab 7 (Sources_Log) complete and fully sourced. Sign-off before continuing.
2. Milestone 2: Tabs 3, 4, 5 (permits, supply, trade economics).
3. Milestone 3: Tabs 2 & 6 (scoring + CAC) plus the Sources & Method doc and a 20-minute walkthrough call.

DEFINITION OF DONE
- Every number traces to a source in Tab 7.
- Estimates/benchmarks labeled vs. hard local figures.
- No fabricated cells; gaps flagged, not filled.
- Formulas (not hard-coded values) for calculated fields; weights editable.
- Clean formatting: frozen headers, number formats, conditional formatting on the score tab.

TO APPLY, TELL US BRIEFLY
1. Your experience pulling Census/ACS data by ZCTA (sample link welcome).
2. Whether you've used Google Keyword Planner for local CPC research.
3. Any experience with government license/permit datasets.
4. Your fixed-price bid and rough timeline.

Reminder: start your proposal with "PIPES."

• Your experience pulling Census/ACS data by ZCTA?
• Whether you've used Google Keyword Planner for local CPC research?
• Any experience with government license/permit dataset?
• Your fixed-price bid and rough timeline?

We are looking for a Python automation engineer to build an automated lead intelligence platform that collects business information from multiple public sources, performs AI-powered website analysis, scores leads, and synchronizes qualified records with HubSpot.

• Describe a similar Python automation or data integration project you have built. What was your role and what technologies did you use?
• How would you collect, normalize, and deduplicate business data from multiple public sources while keeping the solution reliable and maintainable?
• Have you integrated with HubSpot CRM using APIs? If yes, briefly describe what you implemented.
• Please submit a 1–2 minute video introducing yourself, explaining your relevant experience, how you would approach this project, and the biggest technical challenges you foresee. Applications without a video will not be considered.

We are seeking a skilled freelancer to build a list of verified emails for lead generation. The ideal candidate will ensure the data is clean and free of bounces or invalid emails. Experience with data validation and email verification tools is essential. The goal is to create a reliable list that enhances our marketing efforts.

VanHollandRecruit helps European companies hire talent in the United States. Our team handles the personal follow-up. We are looking for a freelance lead researcher who can consistently find high-quality companies with clear US hiring intent.
What you will do (research only)

Find European companies that are actively hiring in the United States, or clearly preparing to hire in the US
Collect proof of US hiring intent (job post link, careers page link, announcement link)
Identify 1 to 3 relevant decision makers per company (CEO, COO, Head of Sales, HR, Talent Acquisition)
Deliver a clean, structured Excel file with qualified leads
No outreach, no messaging, no calls, no appointment setting

Target countries (priority)

Preferably: Netherlands, Germany, France, Spain, Belgium

Other European countries are also welcome if they match the criteria.
What qualifies as a “good lead”

A lead must have:

EU HQ (or strong EU footprint)
Clear proof of US hiring intent (mandatory)
At least 1 relevant contact with LinkedIn URL (mandatory)
Nice to have: employee size 10 to 500, funded startup/scaleup, multiple US roles, expansion news.

Daily deliverable (Excel)

10 to 25 qualified leads per business day. Each row must include:

Lead Score (A/B/C)
Company name, website, HQ country, employee size (range ok), industry
US hiring trigger (short description) + proof link
Role(s) hiring for + US location/state (if available)
1 to 3 contacts: name, title, LinkedIn URL (email optional)
Notes (why it fits)

Excel columns (must follow exactly)

Lead Score (A/B/C)
Company Name
Website
HQ Country
Employee Size (range)
Industry
US Hiring Trigger (short text)
Proof Link (URL)
Role(s) Hiring For
US Location/State
Contact 1 Name
Contact 1 Title
Contact 1 LinkedIn URL
Contact 1 Email (optional)
Contact 2 Name
Contact 2 Title
Contact 2 LinkedIn URL
Contact 2 Email (optional)
Notes

Quality rules

No proof link = not a lead
No duplicates
No generic lists, every lead must be verifiable
Consistent formatting, clean data

Trial (paid)

Paid trial: 50 leads delivered within 48 hours. If quality is strong, we continue with a weekly or daily cadence.
Required experience

Strong B2B research skills
Comfortable with LinkedIn, job boards, and company career pages (Greenhouse, Lever, Workday, etc.)
Detail-oriented, reliable, consistent delivery

Nice to have

Experience with recruitment lead lists, SDR research, or market research
Familiarity with EU companies expanding to the US

Budget

Open to hourly or per-lead pricing. Please propose your rate and expected daily volume.

• Which sources will you use to find EU companies hiring in the US?
• How will you verify US hiring intent for each lead?
• Can you share a sample lead list you’ve delivered before (redacted is fine)?
• What volume can you deliver per day, and what is your preferred pricing model (hourly vs per lead)?

We are seeking a skilled freelancer to assist with lead generation and list building. The ideal candidate will have experience in identifying and qualifying potential leads, building and managing lists, and ensuring data accuracy. Familiarity with CRM systems and data management tools is essential. The role involves collaborating with our team to develop effective strategies for lead generation and list building.

We are looking for a results-driven Lead Generation Expert to help us grow our client base and connect with businesses that need professional bookkeeping, accounting, payroll, and financial support services.

What we're looking for:
✔ Proven experience generating qualified B2B leads
✔ Experience with LinkedIn outreach, email campaigns, and prospecting
✔ Knowledge of CRM tools and lead management
✔ Strong communication and follow-up skills
✔ Ability to consistently deliver high-quality appointments and leads

Bonus if you have experience selling:

Bookkeeping services
Accounting or CPA services
Payroll solutions
Tax preparation
Financial consulting

If you have a track record of helping service-based businesses generate qualified leads, we'd love to hear from you.

📩 Send your resume, portfolio, or a brief summary of your experience in the comments or via direct message.

I need a lean MVP that automatically hunts for conversations where my web app can be mentioned in a helpful, brand-building way. The workflow is straightforward:

1. Crawler
• Scan Reddit plus Google News (blogs and articles surfaced).
• Harvest threads and comments.

2. AI Scoring
• Rank each conversation primarily on its relevance to the app and the overall popularity of the post or thread.
• Ignore low-signal chatter; keep only high-potential mentions.

3. Drafting Replies
• Use an LLM to generate a concise, promotional reply that feels organic and value-adding, not spammy.

4. Dashboard Review
• Queue the top-scoring replies in a simple web dashboard.
• I must be able to edit any draft before it goes live and quickly filter or sort the queue (by score, subreddit, date, etc.).

After approval, publishing back to Reddit is required; auto-posting to blog comment sections or other sources can wait until a later phase. Brand awareness is the driving metric, so analytics are “nice to have” but not mandatory for this first milestone.

Tech stack is your call—Python with PRAW, BeautifulSoup, and an OpenAI or similar API would work fine—but keep it modular so more sources and scoring signals (sentiment, performance analytics) can plug in later.

Deliverables
• Source code with clear setup instructions
• Deployed MVP accessible via a secure URL
• Brief hand-off doc outlining how to extend sources or scoring rules

Acceptance criteria
✓ Finds at least 80 relevant Reddit threads and 20 Google News items during a test run
✓ Produces AI replies for each, sorted by score in the dashboard
✓ Lets me edit, approve, or reject and then publishes approved replies back to Reddit without errors

Skills: Python, Web Scraping, Data Mining, Web Development, Frontend Development, Data Analysis, API Development, Natural Language Processing

I am looking for 500 contacts/email addresses for property damage claim managers in Iowa, United States. The claim managers should be in the field of property damage (wind, hail, tornado, fire, structural, water, etc.).

I am looking for 500 contacts/email addresses for property damage claim managers in Wisconsin, United States. The claim managers should be in the field of property damage (wind, hail, tornado, fire, structural, water, etc.).

I am looking for 500 contacts with name, company, and email addresses for independent adjusters located in Wisconsin, United States. The independent adjusters should specialize in property damage claims.

I am looking for 500 contacts with name, company, and email addresses for independent adjusters located in Iowa, United States. The independent adjusters should specialize in property damage claims.

I need an excel list of name, company, and email address for all licensed attorneys in Wisconsin. There may be additional assignments after this one depending on product. I am looking for 500 contacts of attorneys that specialize in construction law, real estate law, property law, and property insurance law, or similar fields.

We're an early-stage B2B technology company operating in the AI and data infrastructure space and are looking for an experienced lead generation specialist to help build highly targeted prospect lists for outbound sales campaigns.

This is not a generic list-building project. We already have clearly defined Ideal Customer Profiles (ICPs) and need someone who can research companies, identify the right decision-makers, and deliver clean, verified contact data.

Responsibilities
Research companies that match our predefined ICPs
Identify the most relevant decision-makers within each organization
Find and verify business email addresses
Deliver structured CSV files ready for outbound campaigns
Flag any notable company insights where relevant
Initial Deliverable

CSV including:

First Name
Last Name
Company
Job Title
Work Email (verified)
LinkedIn Profile
Company Website
Industry
Company Size
Country
Ideal Experience

We're looking for someone with proven experience supporting B2B SaaS or enterprise technology companies, ideally within one or more of:

AI
Machine Learning
Data Infrastructure
Enterprise Software
Data Platforms
Developer Tools
Cloud Infrastructure

Experience building prospect lists for companies selling into enterprise technology teams is highly preferred.

Tools

Experience with one or more of the following is preferred:

Apollo
Clay
LinkedIn Sales Navigator
ZoomInfo
RocketReach
Lusha
Instantly
NeverBounce
ZeroBounce

You're welcome to use your own workflow as long as the output is accurate.

Success Criteria
Highly relevant companies matching our ICPs
Correct decision-makers
Verified business email addresses
Low bounce rate
Clean, well-organized CSVs

This is expected to become an ongoing engagement as we expand into additional customer segments.

Please include in your proposal:

A brief summary of similar projects you've completed
The tools you use to source and verify contacts
How you ensure email accuracy and low bounce rates
An example (or anonymized sample) of a prospect list you've previously delivered

Job Title

Acquisition Research Specialist (UK SMEs)

About Us

Fernraven Holdings Ltd is a UK acquisition vehicle focused on identifying and acquiring established, high-quality privately owned businesses for long-term ownership.

Our current focus is on UK businesses operating within Fire Safety, Electrical Compliance, HVAC, Facilities Maintenance, and other recurring B2B compliance service sectors. Our objective is to build a proprietary database of acquisition opportunities rather than purchasing generic lead lists.

The Role

We are seeking an experienced B2B Research Specialist to help identify companies that match our acquisition criteria.

This is not a simple data-entry project. We are looking for someone with excellent research skills who can identify high-quality businesses using public sources, verify information carefully, and present findings in a structured format.

The successful freelancer will become a long-term research partner as our acquisition pipeline expands.

Initial Test Project

The engagement will begin with a paid test task consisting of 5 carefully researched UK companies that match our criteria.

Successful completion of this project will lead to ongoing research assignments.

Responsibilities

Your responsibilities will include:

Researching UK businesses within our target sectors.
Identifying companies that match our investment criteria, including:
Sector
Business maturity
Geographic location
Management structure
Indicators of stable, recurring commercial activity
Verifying decision-maker information.
Producing accurate, well-organised research suitable for import into our CRM/database.
Deliverables

For each company identified, please provide:

Company Name
Company Website
Industry / Business Description
Company Location
Managing Director, Owner or Founder
Professional Email Address (where publicly available)
Telephone Number
LinkedIn Profile (company and decision-maker if available)
Companies House Link
A brief 2–3 sentence explanation describing why the company appears to match our acquisition criteria.

Accuracy is significantly more important than quantity.

Ideal Experience

We are looking for freelancers with experience in one or more of the following:

B2B Lead Research
Market Research
M&A Research
Business Acquisition Research
Corporate Finance Research
Investment Research
CRM Database Building

Experience researching UK SMEs is highly desirable.

How to Apply

Please include the following in your proposal:

A brief summary of your experience with B2B lead generation or acquisition research.
One example of a research project where you had to locate difficult or non-obvious business information.
The research tools you typically use (for example Companies House, LinkedIn Sales Navigator, Apollo, Clay, Google, industry directories, etc.).
Screening Question

Have you previously completed research projects involving UK business acquisitions, corporate finance, investment research, or B2B lead generation? Please briefly describe one example.

Important Note

This is a quality-first engagement.

We are looking for a reliable long-term research partner rather than the lowest-cost provider. Strong performance on the initial paid test task will lead to ongoing work as we continue expanding our acquisition pipeline.

Need someone to data mine a list of names for email addresses and phone numbers. The list contains over 1,000 names, and efficiency and accuracy are crucial. The ideal candidate will have experience in data mining.

In the message- let me know how long this will take you to finish

About the Project:
We have developed a powerful, fully automated B2B Lead Generation Software called "Tradbook". The tool extracts high-quality business leads and data seamlessly from Facebook, Instagram, and YouTube. It is built for digital marketers, real estate agencies, and small to medium business owners worldwide who need high-converting B2B prospects.

What We Are Looking For:
We are looking for Experienced, high-driven Outbound Sales Partners, Digital Marketers, and Affiliate Marketers who can promote and sell this software globally (with an initial focus on India, UAE, and USA markets).

Payment Model (Strictly Commission-Based):
Please note: This is a 100% Commission-Based Sales Role. We are NOT offering any fixed monthly salaries or fixed budgets at this moment.
• You will earn a massive 40% to 50% commission on every single license/sale you close.
• Since this is a high-demand B2B tool, your earning potential is completely unlimited.
• Track your conversions easily via a custom promo/affiliate code.

Requirements:
• Prior experience in software sales, B2B lead generation, or outbound marketing.
• Ability to reach out to potential buyers via LinkedIn, Email, or Social Media.
• Great communication skills to pitch the benefits of automated data extraction.

If you are a self-starter who wants to earn a lucrative percentage on every sale, we would love to partner with you. Let's grow together!

Join our commercial cleaning company to help us become a data-driven organization. We are seeking a detail-oriented Data Analyst to work with our team to analyze and interpret data, identify trends, and provide actionable insights to improve our operations. Your work will directly contribute to our growth and efficiency. If you have a passion for data and a keen eye for detail, we would love to hear from you!