Data Scraping Projects on Vollna

We are subscribed to "Bright Data" and we need someone to create a simple re-usable script via "Bright Data's Scraper Studio" that will visit the same website (every time) and extract the following attributes:

AVAILABILITY
PRICE
PRODUCT LISTING PAGE URL

The input will be in the form or a .csv file. COL A in the .csv file will contain SKUs. The script will need to take each SKU from the .csv file, search it in the website's search bar, verify that the SKU is an exact match, visit the product page and then extract the data. If the SKU does not exist, then skip the row and move to the next row.

URL: https://ikonmotorsports.com/

Summary
Eco Clean Bay is an eco-friendly cleaning company serving the Bay Area, specializing in vacation rental turnovers and expanding into recurring commercial contracts — office buildings, senior living facilities, schools, and property management portfolios. We're looking for a motivated, commission-only sales rep to prospect, pitch, and close new recurring clients.

Responsibilities: prospecting and outreach to property managers, facility managers, and building operators; pitching Eco Clean Bay's recurring cleaning services; closing contracts worth $500 or more in monthly recurring revenue; handing off signed clients to our operations team for onboarding.

Compensation: 10% commission on each client's first three months of invoiced revenue, paid out as those invoices are collected. No cap on deal size — bigger contracts mean bigger payouts. This is a 100% commission role with no base pay.

Ideal candidate: experience in B2B or facilities sales, comfortable with cold outreach, self-directed, Bay Area market knowledge a plus.

We run a B2B referral sales program. Our clients are growth-stage B2B companies, and our network of referral partners (we call them connectors) introduces those clients to the right buyers. The whole thing works only if we can quickly tell a connector “here are the 10 companies in your network worth an intro.” Right now building those lists takes days and the output is messy. We want someone who does this for a living to fix it and then run it.

What you’ll do

Build and maintain a large, accurate target company list in Apollo that matches our ICP. That means knowing which Apollo filters and data points can be trusted and which can’t (revenue on private companies is usually wrong, headcount can mislead), and working with keywords, negative keywords, and lookalikes to cut out agencies, services firms, publishers, tiny PLG startups, and niche vertical plays.

Layer in outside signals to improve accuracy, such as recent funding rounds (Term Sheet, Axios Pro Rata, Next Play and similar), investor patterns, years in business, and G2 presence as a legitimacy check.

Take connector network exports (LinkedIn connections, CRM lists) and match them against the target list, then hand us a short, clean shortlist we can approve in minutes.

Set up and run the workflow in Google Sheets and Claude, including the Apollo MCP connection to Claude. We want one organized system with clear ICP definitions, exclusion rules, and consistent columns: company, website, LinkedIn link (clickable), funding stage, size, short fit note, and which connector knows whom.

Keep it current. Companies raise, pivot, rename, and get acquired, so this is an ongoing job, not a one-time list.

Who we’re looking for

You’ve done serious list building and enrichment in Apollo and can explain its quirks without looking them up. You are comfortable using Claude (or similar) to automate research and cleanup, and you’re strong in Google Sheets. Most importantly, you take ownership. We’ll give you direction and context, and we expect you to tinker, research, test, and come back with a better approach than we asked for. If you need step-by-step instructions for every task, this won’t be a fit.

Engagement

We’d like to start with a paid trial project: build a first-pass target list against our ICP and run one connector match. If that goes well, this becomes an ongoing role at roughly 20 hours per week with a goal of making this more within a few months. Interviews will be with both co-founders.

Overview
I run a group therapy practice in New York and am launching a therapist directory site. I need a clean, deduplicated database of licensed mental health clinicians in New York State, built in phases by region. I also need the script handed over so I can refresh it later.



Phases (each one a separate milestone)



Central NY: Onondaga, Tompkins, Cortland, Cayuga, Oswego, Madison, Seneca, Tioga
Rochester and Finger Lakes (Monroe, Ontario), plus Buffalo (Erie, Niagara)
Capital Region (Albany, Saratoga, Schenectady, Rensselaer), plus Binghamton (Broome)
Hudson Valley (Ulster, Dutchess, Orange, Westchester, Rockland)
Long Island and NYC (all five boroughs)



License types: LCSW, LMSW, LMHC, LMFT, licensed psychologist, PMHNP, licensed creative arts therapist



Approved sources only



NPPES NPI Registry bulk data (filter by NY and the relevant taxonomy codes)
NYSED Office of the Professions online license verification
Clinicians’ and group practices’ own public websites, for email and specialties



Feel free to use: Psychology Today, Headway, Zocdoc, thrivingcampus.com, professional association directories, listservs, or any login-gated or members-only page.



Fields per record
First name, last name, credential, license number and status, practice name, street address, city, county, ZIP, phone, website, public email (if listed), specialties (if listed), telehealth (Y/N, if listed), data source, and date collected.



Deliverables per phase



A Google Sheet or CSV, deduplicated by NPI and license number
A short summary: record count, and the percent of records that include an email
At the end: a documented, re-runnable script (Python preferred) with setup instructions



Requirements



Demonstrated experience with NPPES data or other public records
Accuracy over volume. I’ll spot-check about 25 records per phase.



Screening questions



Have you worked with the NPPES NPI bulk file before? What taxonomy codes would you use for these license types?
How will you deduplicate clinicians who appear at more than one practice address?
Roughly what percent of records do you expect to include an email address, and how would you find them?



Budget: based on hourly work

# Social Media Scraping & Outreach Automation Specialist | Instagram, X, Facebook | Existing Tools Required

**Part-Time | Long-Term Monthly Retainer | Remote**

I'm looking for a highly experienced automation technician to manage scalable lead generation, data scraping, and social media outreach systems for multiple online businesses.

**This is NOT an entry-level VA position, and I'm NOT looking for someone to learn automation on my dime.**

I'm specifically looking for someone who has **already developed or operates their own custom automation tools, scripts, and proven workflows** and can adapt those systems to my businesses.

### What I Need

- **Advanced scraping:** Extract and organize targeted prospect data from websites, social platforms, directories, and other accessible sources.
- **Social automation:** Extensive hands-on experience with outreach workflows on Instagram, X (Twitter), and Facebook.
- **Custom infrastructure:** Strong preference for proprietary Python scripts, browser automation, APIs, and self-hosted systems over expensive third-party subscriptions.
- **Platform expertise:** Deep familiarity with platform limitations, rate limits, account health, restrictions, troubleshooting, and maintaining reliable operations as platforms change.
- **Ongoing management:** Monitor workflows, diagnose failures, maintain integrations, and optimize performance with minimal supervision.
- **Scalability:** Experience operating high-volume lead generation and personalized outreach pipelines while respecting applicable platform requirements.

### Ideal Candidate

You already have a working automation stack that you've deployed successfully for other projects.

You understand the technical challenges of running reliable scraping and outreach infrastructure across major social platforms.

You can demonstrate real-world results, maintain your own systems, and proactively address technical problems.

**I am NOT looking for someone who primarily relies on PhantomBuster, Apify, or expensive SaaS subscriptions.** Custom-built, low-overhead infrastructure is strongly preferred.

### Compensation

I'm looking for an affordable, long-term **fixed monthly retainer** covering ongoing operations, monitoring, troubleshooting, and maintenance.

Minor initial configuration is expected, but I strongly prefer existing tools and workflows over expensive custom development.

### To Apply, Please Answer:

1. **What proprietary scraping or outreach tools have you personally built or currently operate?**
2. What is your direct experience with Instagram and X automation?
3. Can you provide a short demonstration of existing working systems?
4. How do you handle platform changes, rate limits, account restrictions, and unexpected automation failures?
5. What third-party subscriptions, servers, or other ongoing expenses would your system require?
6. What is your proposed monthly retainer to manage and maintain the complete operation?

**Applications with demonstrated working systems will receive priority. Generic automation agencies and beginners need not apply.**

I'm looking for a reliable long-term technical partner who can take ownership of daily operations while I focus on growing the businesses.

Overview
I run a group therapy practice in New York and am launching a therapist directory site. I need a clean, deduplicated database of licensed mental health clinicians in New York State, built in phases by region. I also need the script handed over so I can refresh it later.



Phases (each one a separate milestone)



Central NY: Onondaga, Tompkins, Cortland, Cayuga, Oswego, Madison, Seneca, Tioga
Rochester and Finger Lakes (Monroe, Ontario), plus Buffalo (Erie, Niagara)
Capital Region (Albany, Saratoga, Schenectady, Rensselaer), plus Binghamton (Broome)
Hudson Valley (Ulster, Dutchess, Orange, Westchester, Rockland)
Long Island and NYC (all five boroughs)



License types: LCSW, LMSW, LMHC, LMFT, licensed psychologist, PMHNP, licensed creative arts therapist



Approved sources only



NPPES NPI Registry bulk data (filter by NY and the relevant taxonomy codes)
NYSED Office of the Professions online license verification
Clinicians’ and group practices’ own public websites, for email and specialties



Feel free to use: Psychology Today, Headway, Zocdoc, thrivingcampus.com, professional association directories, listservs, or any login-gated or members-only page.



Fields per record
First name, last name, credential, license number and status, practice name, street address, city, county, ZIP, phone, website, public email (if listed), specialties (if listed), telehealth (Y/N, if listed), data source, and date collected.



Deliverables per phase



A Google Sheet or CSV, deduplicated by NPI and license number
A short summary: record count, and the percent of records that include an email
At the end: a documented, re-runnable script (Python preferred) with setup instructions



Requirements



Demonstrated experience with NPPES data or other public records
Accuracy over volume. I’ll spot-check about 25 records per phase.



Screening questions



Have you worked with the NPPES NPI bulk file before? What taxonomy codes would you use for these license types?
How will you deduplicate clinicians who appear at more than one practice address?
Roughly what percent of records do you expect to include an email address, and how would you find them?



Budget: based on hourly work

We are looking for a high-performing, sales-focused professional to help grow our live senior services marketplace:

Young & Blissful https://youngandblissful.com/

Please review the marketplace before applying.

We already have 5,000+ businesses listed on the platform.

The foundation has been built.

Your primary responsibility is now to turn those listings and new business opportunities into:

Claimed Listings → Verified Profiles → Paid Subscription Plans → Recurring Revenue

This is primarily a sales, HubSpot CRM, outreach, follow-up, automation, and conversion role.

Role Breakdown

90% — Sales, Outreach & Revenue Generation

Your main responsibility is to generate revenue.

You will:

Contact a high volume of businesses by phone and email.

Work from our existing database and continuously build new opportunities.

Reach business owners, managers, and decision-makers.

Explain that their business is already listed on Young & Blissful.

Guide providers through the listing-claim process.

Encourage businesses to complete and verify their profiles.

Present relevant paid subscription options.

Convert free listings into paid plans.

Follow up consistently until there is a clear outcome.

Re-engage old leads and inactive opportunities.

Schedule demonstrations or meetings when needed.

Identify multi-location, partnership, advertising, and upsell opportunities.

Manage the entire sales pipeline in HubSpot CRM.

Record every meaningful interaction, outcome, and next step.

Use HubSpot tasks, templates, sequences, lists, workflows, and reporting.

Build and improve outreach automations.

Help create AI-assisted sales agents or workflows where appropriate.

Continuously improve conversion scripts, objection handling, and follow-up sequences.

High-volume outreach is expected.

You should be comfortable handling:

significant call volume;

high-volume personalized email outreach;

repeated follow-up;

multiple lead stages;

large CRM lists.

However, results matter more than activity.

We do not measure success simply by how many calls or emails you send.

Your success is primarily measured by:

claimed listings;

verified listings;

paid subscriptions;

recurring revenue;

conversion rate;

pipeline growth;

revenue generated.

Performance & Compensation Philosophy

Although the role may begin with an hourly structure, this is a performance-driven position.

We care most about the revenue and conversions you produce.

Compensation may include a combination of:

hourly pay;

sales-performance bonuses;

subscription conversion bonuses;

revenue-based incentives;

expanded hours and responsibility for strong performers.

The long-term opportunity is designed to reward someone who can consistently turn outreach into revenue.

5% — Data Scraping, Verification & List Building

You will also support the quality and growth of our provider database.

Tasks may include:

scraping publicly available business data;

finding new senior-service providers;

identifying business owners or decision-makers;

verifying email addresses;

verifying phone numbers;

checking websites;

validating business location and service information;

identifying duplicates;

correcting incomplete records;

enriching HubSpot contact and company records;

organizing leads into relevant categories and locations.

Accuracy is very important.

We do not want large lists filled with poor-quality or unverified data.

Automation

You should be comfortable helping improve data workflows using:

HubSpot automation;

AI agents;

scraping tools;

enrichment tools;

email-verification tools;

workflow automation platforms.

The objective is to reduce repetitive manual work while keeping data quality high.

5% — Marketing & Social Scheduling

This is a small part of the role.

You may occasionally:

schedule approved LinkedIn posts;

schedule Instagram and Facebook posts;

upload approved videos or graphics;

add prepared captions and hashtags;

schedule marketplace promotional content;

confirm posts published correctly;

support simple provider-promotion campaigns.

Most content and marketing direction will already be provided.

This is not a Social Media Manager role.

HubSpot Experience Is Essential

We are specifically looking for someone with strong practical HubSpot experience.


AI, Automation & Agent Skills

We want someone who thinks about how technology can improve sales productivity.

You should be comfortable using AI for:

lead research;

prospect qualification;

email personalization;

call preparation;

follow-up messaging;

objection handling;

data enrichment;

reporting;

workflow optimization;

sales automation.

Experience with tools such as:

ChatGPT

Claude

Gemini

Perplexity

HubSpot AI

Zapier

Make

scraping tools

email-verification tools

AI agents

and Asana

is valuable.

We are particularly interested in someone who can recognize repetitive work and ask:

“Can this part of the workflow be automated?”

What We Are Looking For

You have:

Proven outbound sales or business-development experience.

Strong HubSpot CRM experience.

Confidence making business calls.

Experience with high-volume email outreach.

Strong follow-up discipline.

Excellent professional English.

Experience managing large lead lists.

Ability to sell without being overly aggressive.

Strong organization and CRM accuracy.

Ability to work independently.

A revenue-focused mindset.

Comfort using AI and automation.

Good judgment when researching and verifying business information.

Experience with any of the following is especially valuable:

subscription sales;

membership sales;

marketplace sales;

directory listings;

B2B sales.

Sales Approach

Our preferred approach is:

Professional → Consultative → Persistent → Helpful → Conversion-Focused

Providers should clearly understand:

that their business is already listed;

why claiming the profile matters;

how verification may strengthen the listing;

what additional features are available;

why a paid subscription may be valuable.

We do not want aggressive telemarketing.

We do want someone who confidently asks for the next step and the sale.

Weekly Performance Reporting

Your weekly report should include:

businesses contacted;

decision-makers reached;

calls completed;

emails sent;

follow-ups completed;

meetings booked;

listings claimed;

listings verified;

paid upgrades;

new recurring revenue;

conversion rate;

pipeline value;

lost opportunities and reasons;

data records added or verified;

automation improvements implemented.

Important

Activity metrics help us understand the pipeline.

Revenue and conversion metrics determine success.

Someone completing 300 activities with no conversions is not outperforming someone completing 100 high-quality activities that produce subscriptions.

Tools

You may work with:

HubSpot CRM

Asana

Google Sheets

LinkedIn

Publer

Facebook

Instagram

Canva

ChatGPT

AI automation tools

scraping and data-verification tools

Working Style

You should be:

highly sales-driven;

persistent;

organized;

accountable;

comfortable with targets;

proactive;

confident on calls;

comfortable managing high volumes of leads;

able to work independently;

interested in improving systems;

comfortable using automation;

motivated by measurable growth and revenue.

You should not require daily reminders to follow up with your pipeline.

Hours & Compensation

Starting at approximately 10 hours per week

Monday–Friday

Flexible schedule

Some availability during Ontario / Eastern Time business hours

Long-term opportunity

Additional hours based on performance

Contract-to-hire potential

Compensation

Initial compensation may be hourly.

Longer-term compensation will be structured around a combination of:

Hourly Pay + Performance Bonus

Strong sales performance can lead to:

higher earnings;

additional hours;

increased responsibility;

sales bonuses;

revenue-based incentives.

Paid Trial

A small paid Upwork trial may be used to evaluate:

HubSpot ability;

sales thinking;

outbound communication;

follow-up strategy;

data research and verification;

automation thinking;

objection handling;

organization;

reporting quality.

To Apply

Please answer the following:

Need a freelancer to scrape LinkedIn for current and former employees of two companies, with a total of less than 5,000 profiles. The work includes collecting relevant employee information and organizing the data into a clean, structured format. Please share examples of similar projects and your approach to handling LinkedIn data responsibly.

I need a clean, well-structured spreadsheet that combines two distinct lead pools: apartment locator / rental real-estate agents and car sales professionals. For every contact, include the full name, company, phone number, and website exactly in separate columns.

Coverage must be truly nationwide—pulling from multiple states across the country, not just one region—so the final file represents a broad, diversified prospect list. Please scrape only publicly available, up-to-date information from reliable sources such as brokerage directories, dealer listings, LinkedIn, Google Maps, or other reputable platforms, and remove any duplicates you find.

Timing is critical: an initial batch is needed as soon as possible, with the complete list delivered shortly after. I’ll verify a random sample for accuracy, so aim for a high validity rate on phone numbers and web links. Provide the data in Excel or CSV, clearly separating the two industries on different tabs or files.

Skills: Data Entry, Excel, Web Scraping, Web Search, Data Scraping, Data Analysis, Data Management, Data Annotation

We're looking for a developer to help us build an automated new-build real estate data platform for a real estate client in Ontario, Canada.

The goal is to create a system that automatically collects new construction project information from builders across Ontario, including new releases, pricing, availability, floor plans, and incentives, and displays it on a searchable website.

**Our biggest priority is speed.** We want to be among the first to know when a builder releases new inventory, updates pricing, changes availability, or announces new incentives. Ideally, the system would detect these changes as close to real time as technically possible, notify us immediately, and update the website with minimal delay.

We're exploring whether this could be achieved through web scraping, APIs, direct data feeds, or a combination of approaches. We'd like your recommendations on the best way to achieve this, including any limitations that might affect how quickly information becomes available.

We'd like to start with a proof of concept covering 5–10 Ontario builders before expanding to more developments across the province.

We're looking for someone with experience in web scraping, data automation, API integrations, and database development.

**Please include:**
- Examples of similar projects you've built.
- How you would detect new releases and price changes as quickly as possible.
- What update frequency is realistically achievable.
- Your estimated cost for an initial proof of concept.
- Any ongoing hosting, maintenance, or

We're looking for an experienced lead generation freelancer to build a high-quality list of privately owned construction companies across the United States.

We're starting a business that helps established companies explore opportunities to license their historical operational data to AI companies. We're looking for construction businesses that have been operating for years and likely have substantial records, including project documentation, estimates, invoices, job histories, and internal communications.

Ideal Company Profile:

Industry: Construction (general contractors, commercial construction, roofing, HVAC, plumbing, electrical, specialty contractors, etc.)

Location: United States

Company size: Ideally 20–500 employees

Years in business: Preferably 10+ years

Ownership: Privately owned, preferably founder- or family-owned

Priority: Established businesses with significant operational histories

Information Required for Each Lead:

Company name

Website

Industry / construction specialty

Headquarters city and state

Estimated employee count

Year founded

Owner, founder, CEO, or president's name

Verified direct phone number (strongly preferred)

Verified business email address

LinkedIn profile of decision-maker

Source URLs for verification

What We're Looking For:

We care much more about quality than quantity. We want accurate, actionable leads for direct phone outreach—not a generic database dump with outdated contact information.

Please deliver the leads in a clean Google Sheet or Excel file.

Initial Project:

We're looking to start with a paid test of 50 leads, with the opportunity to expand to 500–1,000+ leads and ongoing work if the quality is strong.

When Applying, Please Include:

Your experience building B2B lead lists.

Which tools you use (Apollo, LinkedIn Sales Navigator, Clay, ZoomInfo, etc.).

How you verify phone numbers and email addresses.

Your price per 100 verified leads.

A sample of similar work you've completed.

We're looking for someone reliable who can become a long-term partner as we scale.

Need a freelancer to scrape prices from multiple websites using a large list of URLs. The work includes extracting product prices, handling a high volume of requests, and organizing the results clearly. Please share relevant experience with similar scraping projects and your approach to managing large-scale data collection efficiently.

I’m looking for a reliable and detail-oriented Real Estate Data Research Specialist to research U.S. real estate properties, verify property information, and organize accurate data in spreadsheets.

Tasks
Research residential and rental properties online.
Collect property addresses, prices, rental rates, and other relevant details.
Research comparable properties and market pricing.
Verify property information using reliable online sources.
Gather property details from websites such as Zillow, Realtor.com, and Redfin.
Organize and update property data in Excel or Google Sheets.
Check data for accuracy, missing information, and duplicates.
Maintain clear records and include research sources where needed.

Requirements
Experience in real estate or online data research.
Familiarity with the U.S. real estate market is a plus.
Good knowledge of Excel or Google Sheets.
Strong attention to detail and data accuracy.
Ability to follow instructions and communicate clearly.

We are looking for an experienced Facebook Group Data Scraping and Lead Generation Specialist to collect up to 5,000 business contact records by November 10, 2026.

We will provide the Facebook groups to research. Your role will be to identify businesses represented by group members and collect their publicly available business contact information using permitted research methods.

Required Data

All information must be delivered in a Google Sheet with the following four columns:

Business Name
Email Address
Business URL (Website)
Phone Number
Requirements

Research the Facebook groups provided to identify relevant businesses.

Collect up to 5,000 business contact records.

Find and verify business information using publicly available sources.

Ensure all contact details are accurate and up to date.

No duplicate businesses or records.

No fabricated or unverified information.

Use compliant research methods without unauthorized collection of private Facebook member information.

Deliver all information in one organized Google Sheet.

Deadline

November 10, 2026

We would like the full dataset completed by this date, with progressive delivery as records are collected.

When Applying

Please provide:

Your experience with Facebook group data research and lead generation.

The tools and methods you use to collect and verify business contact information.

Your total price for up to 5,000 completed records.

Your estimated number of records per day.

Confirmation that you can meet the November 10 deadline.

We are looking for someone who can start immediately and deliver accurate, high-quality business contact data within the required timeframe.

I need help scraping Keller Williams to collect a complete list of agents and brokers across North America. The website currently shows only 6–10 agents per page, but I want the full dataset. Manual collection is not practical due to the size of the list, which includes over 150,000 agents. I’m looking for someone who can extract this data efficiently and organize it for easy use.

We’re looking for someone to identify 20 potential clients based on our target customer criteria.

For each company, we need the company name, website, relevant decision-maker’s name and job title, and their professional email address.

The goal is to build a targeted list of potential clients that match our ideal customer profile, with accurate, up-to-date contact information ready for outreach.

We are seeking a skilled web scraping expert to assist with a gathering reviews from Korea based platform - https://seoulpi.io/article. The ideal candidate should have experience in data gathering from the complex websites.

The platform would need to verify korea based mobile number. You would need to arrange it.

We are looking to get the below datapoints:

Source Url, Breadcrumbs, Title, Sub Title, Published Date, Author, Social Media Link, Article Text Tags.

Please share a sample file, if this is of your interest.

I have our company’s 2026 sales sitting in multiple Excel and CSV files and I want to turn that raw information into an interactive Power BI dashboard that management can rely on to grow revenue and cut waste.

First, the data needs a full scrub: deduplicate records, handle missing values, and standardise formats. You’re free to use Text to Columns, Flash Fill, or Power Query—whichever combination gets us a clean, reliable dataset ready for modelling.

Once the data is ready, build a Power BI report that surfaces the indicators we care about most:
• إجمالي المبيعات والأرباح
• أداء المنتجات، العملاء، والمناطق
• التكاليف، الخصومات، والمرتجعات
• النسب المئوية المفيدة للمقارنة
• فلاتر ديناميكية للمناطق والشهور

The finished deliverables I expect are:
1. The cleaned, well-documented dataset (Excel or CSV).
2. The PBIX file with all measures, visuals, and relationships clearly labelled.
3. A published Power BI link (or .pbit template) that managers can explore without editing rights.
4. A short insights memo highlighting trends, anomalies, and quick-win recommendations.

Accuracy, performance, and a layout that tells a clear story are critical for acceptance.

Skills: Visual Basic, Data Processing, Data Entry, Excel, Statistics, Data Scraping, Data Visualization, Data Analysis, Power BI, Data Management

I run a trading company that supplies steel pipes from a factory. I need someone to find the people who buy steel pipe at companies in the Gulf and Middle East or other regions, and add them to my spreadsheet with verified work emails.

What we sell: steel pipes for oil & gas wells, pipelines and water wells (casing, tubing, line pipe, well screens).

Where to look (priority order):

Saudi Arabia, UAE, Kuwait, Oman, Qatar, Bahrain (main focus, at least 50% of leads)
Iraq
Egypt, Türkiye, Pakistan, Africa (only after the above)

Companies to target: pipe stockists and traders, oilfield service companies, oil & gas producers, pipeline contractors, and water-well drillers

People to find: Owner/MD, Procurement Manager, Purchasing Manager, Supply Chain Manager

Do not include: pipe manufacturers, government oil companies (Aramco, ADNOC, etc.), US/Canadian companies, personal emails, or generic info@ addresses

What I provide:

A ready made Excel sheet with a 2 minute guide
44 starter companies, including 11 confirmed buyers with current projects
A Status column that automatically checks each lead for missing details, duplicates and email verification

What I need:

300 leads showing ✅ Ready in the sheet
Each email checked with NeverBounce, ZeroBounce or Hunter, with at least 80% valid
Only business contact details from public sources (LinkedIn, company websites, directories)

Payment: per ✅ Ready lead. We start with a paid trial of 30 leads. If the quality is good, you’ll complete the remaining 270.

To apply, please tell me:

A similar B2B or industrial lead gen project you’ve done
Which tools you use (Apollo, LinkedIn Sales Navigator, Hunter, etc.)
Your price per verified lead
How long 30 leads and 300 leads would take

We have an existing list of companies in a Google Sheet and need a meticulous Data Researcher to build out our outreach database. Your job is to research each company on the list, identify the correct decision-maker handling their marketing and partnerships, and extract their direct contact information.
We are targeting individuals holding the following titles (or equivalent):
• Influencer Marketing Manager / Lead
• Brand Partnerships Manager / Director
• Public Relations (PR) Manager / Director
• Marketing Director / Marketing Manager

Scope of Work

For each company provided in our Google Sheet, you will research and fill in the missing fields with accurate, up-to-date data:
• Full Name of the target professional
• Direct Business Email Address (No generic info@ or contact@ emails)
• Direct Phone Number / Extension (If available)
• Individual LinkedIn Profile URL

Required Skills & Tools

• Proven experience in B2B Lead Generation and Data Mining.
• Expert-level navigation of LinkedIn Sales Navigator to locate the exact job titles needed.
• Proficiency with email verification and scraping tools (e.g., Apollo.io, Hunter.io, RocketReach, Findymail).
• Strict attention to detail data must be clean, accurately formatted, and verified to prevent bounces.
• Ability to work directly within Google Sheets.

Deadline: Saturday

To Apply

Please submit a brief proposal outlining your experience with similar B2B lead generation projects. Let us know what data-mining tools you currently use. Bonus points if you include a small sample (2–3 leads)

I am preparing a direct outreach campaign and need a clean, up-to-date spreadsheet of the leading M&A intermediaries that regularly place mid-sized private businesses on the market. My priority regions are the United Arab Emirates (with particular focus on Dubai and Abu Dhabi), Australia and key European hubs, followed by any other English-speaking jurisdictions you identify.

The list must include firms that sell mid-sized private businesses as well as reputable business brokers and specialist M&A advisory houses; large investment banks are not my target. Within those firms I need the decision-makers—typically partners, managing directors or heads of origination—together with their direct email addresses (no info@ aliases) and, where available, phone numbers or LinkedIn URLs.

Although my ultimate acquisition brief centres on wholesale, B2B distribution businesses with at least AUD 3 million in annual net profit—ideally in the health & wellbeing space—please capture every intermediary who routinely handles deals in that size bracket; sector specialisation is a nice-to-have, not mandatory.

Deliverables
• An Excel or Google Sheets file with the following columns: Firm Name, City/Country, Website, Contact Name, Job Title, Direct Email, Phone/LinkedIn (if available), Notes on Sector Focus or Recent Deals
• Sources or scrape methodology documented on a separate tab so I can verify accuracy and refresh the data later.

I am happy to answer clarifying questions promptly and can review a small sample before you scale the scrape.

Skills: Data Entry, Excel, Web Search, Market Research, Data Scraping, Google Sheets, Data Collection, Data Management

I need 250 small to mid sized, independent HVAC companies, with the owner’s name and email.

Locations: Minnesota first, then Wisconsin, Iowa, North Dakota, South Dakota.

Include: heating, cooling, and HVAC contractors (plumbing + heating combo shops are OK), independent and locally owned. Exclude: franchises, national brands, manufacturers, multi-location chains, and companies on my exclusion list. (attached)

Columns: Business Name, City, State, Website, Owner First Name, Owner Email, Where Found

Rules:

Find owner names on the company website, Google review replies, Facebook, or the state business registry.

Fill in “Where Found” for every name.

Don’t guess email formats. If there’s no owner email, use the company’s info@ or office@.

Verify emails before delivery.

Process: a paid 10-row sample first, then the rest in two batches.

Budget: $70 fixed.

I have a collection of PDF files that first need to be converted into Excel and then thoroughly cleaned. Once the content is in a workbook, I’ll need you to:

• Remove every duplicate record so each row is unique.
• Apply consistent formatting and sort the data logically for quick reference.
• Split combined fields into individual, clearly-labeled columns where required.

Accuracy is essential; I’d rather it take an extra hour than introduce errors. Please tell me which tool or script you plan to use for the PDF-to-Excel conversion and how you normally validate your results. The final deliverable is a ready-to-use XLSX (or CSV, if you prefer) that is clean, well-structured, and free of duplicates.

Skills: Visual Basic, Data Processing, Data Entry, Excel, Data Scraping, Data Analysis, Data Management, Data Annotation

As the title says, do you have access to Bright Data Web Unlocker?

I'd like you to run some tests against a website (we own the website).

I want to see if we can detect it.

Mainly interested in real-looking browser requests but let me know if there are other options.

I'm only interested in Bright Data Web Unlocker. Please do not bid offering other services. I'm more likely to select you if your bid isn't automated AI slop, as I'd like to hire someone who actually read this post. Thanks for your understanding.

We are looking for an experienced lead generation expert who can develop a reliable system to generate qualified leads for our software services.

Our services include AI/ML development, AI automation, web development, mobile app development, custom software, SaaS, API integrations, and other technology solutions.

Responsibilities:

Research profitable niches and identify potential clients.

Develop a strategy to generate qualified B2B leads.

Build lead generation systems using suitable tools and automation.

Set up effective outreach strategies through email, LinkedIn, and other channels.

Requirements:

Experience building lead generation systems from scratch.

Knowledge of B2B prospecting, market research, and outreach.

Previous experience generating leads for software or IT companies is preferred.

To Apply: Share your previous work, successful case studies, the strategy you recommend, and how you would build a lead generation system for our business.

We are open to long-term collaboration with the right expert.

Project Overview

We are looking for an experienced developer to build a reliable,
maintainable inventory-monitoring and purchasing-assistance tool
for Texas Instruments (TI.com).

This is not a one-time web scraping or Excel export project.
We need a working application that continuously monitors selected
TI part numbers and prepares purchases when our conditions are met.

Our desired workflow is:

Monitor selected part numbers → detect qualifying availability →
recheck price and quantity → add the correct items to the TI.com
shopping cart → fill in approved checkout information → notify
the operator for final review.

Phase 1 must stop before final order submission or payment.
Unattended purchasing is not included in the initial scope.


1. Inventory Monitoring and Configurable Rules

Provide a simple interface to add, edit, import and remove monitored
part numbers, including CSV or Excel import.

Use exact orderable part numbers, including all package and ordering
suffixes. Do not substitute similar products automatically.

For each part number, allow us to configure:
- Desired purchase quantity and minimum available quantity.
- Maximum acceptable unit price and currency.
- Whether partial quantities are acceptable.
- Monitoring priority and an enable/disable switch.

Show the latest available stock, price, applicable purchase limits,
last successful check and current monitoring status.

Distinguish “out of stock” from failed requests, access restrictions
or stale data. A monitoring failure must not be reported as zero stock.


2. Integration Approach and Feasibility

First assess TI’s official inventory, inventory-notification and
ordering APIs, including access approval, quotas and account eligibility.

Use approved official integrations wherever practical.
Any browser automation must be permitted by TI and remain within
the applicable access conditions and limits.

Our primary requested experience is TI.com website cart preparation
and checkout autofill. Do not assume that API order creation is the
same as adding items to the website shopping cart.

Explain which parts of our desired workflow can actually be delivered.
If website cart automation is not permitted or technically feasible,
identify the blocker and propose an API-based approval workflow as
a separately agreed alternative, not a silent replacement.


3. Automatic Cart Preparation and Checkout Autofill

When stock and price meet our rules, revalidate the information
before taking action.

Add the exact approved part number and quantity to the cart.
Respect purchase limits, minimum order quantities and applicable
packaging requirements.

Prevent duplicate additions caused by repeated notifications,
retries or application restarts. Coordinate operations on the same
cart and do not remove or modify unrelated items.

Fill in information from approved company profiles, such as:
company name, contact details, shipping address, billing address,
and purchase-order or tax information where applicable.

Use only information supplied and approved by us.
Do not invent end-customer, end-use or compliance information.

Pause for human intervention when login verification, CAPTCHA,
additional declarations or other unexpected checks are required.

Stop before final order submission or payment and notify the operator.
The operator must be able to review and continue the prepared session.


4. Reliability, Dashboard and Alerts

Design for continuous operation with configurable monitoring,
controlled retries, rate limiting and recovery after interruptions.

Handle expired sessions, API token renewal, timeouts, rate-limit
responses, unavailable stock and unexpected page changes.

For inventory subscriptions, handle initial stock checks,
subscription renewal, expiry and duplicate notifications.

Provide a dashboard showing monitored parts, current status,
recent actions, failures and items awaiting manual review.

Include start, pause, stop and emergency-stop controls.
Send email alerts for qualifying availability, checkout readiness
and failures requiring attention.

Record timestamps so we can measure detection-to-action latency.
Do not promise a refresh interval or monitoring capacity without
explaining the applicable quotas and technical assumptions.


5. Security and Deployment

Deploy the application in an environment controlled by us.

Protect API credentials, login sessions and company information.
Do not store payment-card security codes or expose secrets in logs.

Explain whether the solution runs locally, on a server, or as a
hybrid system, and how the operator takes over the checkout session.

Disclose hosting costs, paid dependencies and recurring service fees.

Bypassing access controls, purchase limits or security challenges,
and using multiple accounts to evade restrictions, are outside scope.


6. Required Experience and Deliverables

Strong experience with Python or TypeScript/Node.js, REST APIs,
OAuth, webhooks and production automation is required.

Playwright or equivalent browser-automation experience is relevant
for any permitted browser-based components.

Experience with TI integrations, electronic-component procurement,
inventory monitoring or e-commerce checkout workflows is preferred.

Experience diagnosing automation failures in Akamai-protected
environments is useful, with appropriate escalation or human handoff.

Deliver complete source code, dependency specifications,
configuration examples, deployment instructions, user documentation,
automated tests and a demonstration of the agreed workflow.

We require maintainable source code, not only a compiled executable
or a tool that depends on an undisclosed developer-owned service.


7. Proposal and Initial Milestone

Please include:
- Relevant projects or a redacted demonstration.
- Your proposed API/browser architecture and required approvals.
- Any limitations affecting TI.com cart and checkout automation.
- Expected monitoring capacity and measurable latency assumptions.
- A milestone-based quote, delivery schedule and maintenance terms.

Start with a small paid feasibility milestone using a few agreed
part numbers. Demonstrate monitoring, rule evaluation and the
permitted purchase-preparation workflow before full development.

Test restock transitions and failures using mocks or available
official test facilities where appropriate. Do not place real
orders during testing without our explicit approval.

We are looking for an experienced Python web data extraction and browser
automation engineer to develop a maintainable website monitoring system.

Required experience:

1. Python web scraping and data extraction
2. Playwright, Scrapy, Puppeteer or Selenium
3. Login sessions, cookies and authorized account workflows
4. Product price, inventory and availability monitoring
5. Scheduled tasks, retries, logging and failure alerts
6. Data export to API, CSV, Excel or database
7. Docker deployment and technical documentation
8. Website structure change detection
9. Experience troubleshooting automation compatibility in environments
protected by Akamai Bot Manager
10. All work must be limited to websites, systems and accounts for which
we have authorization, and must comply with applicable terms,
rate limits and privacy requirements.

The developer must deliver complete source code, deployment documentation,
logging, monitoring and test cases.

Job type: Part-time, freelance
Experience level: Intermediate
Hourly budget: £7–£10
Initial hours: 6–8 hours per week
Duration: Initial 2-week paid trial, with potential for ongoing work
Location: Remote, worldwide

Job Overview

We are a UK-based business developing strategic partnerships with AI-data, data annotation, AI model training and outsourcing companies.

We have already identified an initial list of target companies. We are looking for a skilled researcher who can identify the right decision-makers, obtain and verify professional business contact information, and build an accurate database for our outreach team.

This is primarily a contact research and data enrichment role, not a general market research position.

Key Responsibilities

Research AI-data companies, annotation providers, AI evaluation businesses and outsourcing firms.

Identify relevant decision-makers, including Vendor Managers, Project Managers, Heads of Data Operations, Partnerships Managers, Delivery Directors and Founders.

Find and verify professional LinkedIn profiles and business email addresses.

Use permitted public sources, company directories and licensed B2B databases to collect accurate business information.

Research supplier directories, industry events, exhibitor lists and professional networks.

Identify former employees of companies such as Scale AI, Mercor, micro1, Defined.ai, DataBaker and similar organisations.

Identify consultants and agency founders with established networks in AI project delivery and supplier partnerships.

Remove duplicate contacts and maintain an organised Google Sheets database.

Record the source of each contact, their role and why they may be relevant.

Flag active partnership programmes, vendor applications and potential project-demand signals.

Tools & Skills

Experience with some of the following is advantageous:

LinkedIn and LinkedIn Sales Navigator

Apollo.io

Hunter.io

Snov.io

Google advanced search

Clutch and industry directories

Google Sheets

B2B contact enrichment and email verification


Initial Paid Trial

Research our existing list of AI-data companies and deliver:

10 verified companies.

20 relevant decision-makers.

Available professional email addresses and LinkedIn URLs.

10 former AI-data industry professionals or consultants.

Five industry directories, supplier networks or event sources worth monitoring.

Every entry should include evidence of the person's current role and the contact-information source.

Ideal Candidate

You are detail-oriented, efficient and experienced in B2B lead generation or contact research.

Prior experience researching technology, staffing, AI-data or outsourcing businesses is a plus.

We value accurate, relevant contacts over large volumes of unverified leads.

To Apply

Please answer:

Which tools do you use for B2B contact research and email verification?

Can you provide an anonymised sample of a previous B2B lead database?

Have you researched AI, technology, recruitment or outsourcing companies before?

How many thoroughly verified professional contacts could you reasonably produce in eight hours?

--------------------------------------------------------------------------------------------------------------------
Please begin your proposal with the words AI Partnerships Research so we know you have read the brief.

We are looking for an experienced specialist to help our logistics business generate quality leads and automate our sales process using AI and GoHighLevel.

Responsibilities:

- Generate targeted B2B leads for our logistics services.
- Set up and manage GoHighLevel CRM and sales pipelines.
- Build automated lead follow-ups and nurturing workflows.
- Integrate AI tools to improve lead qualification and outreach.
- Track results and optimize performance.

Requirements:
Proven experience with GoHighLevel, AI lead generation, and CRM automation. Experience in logistics or B2B services is an advantage.

Please share relevant experience and examples of similar projects you have completed.

I need a list of 500 Australian businesses (with employee numbers between 10-50) with the following data:
1. business name
2. business website
3. location (state)
4. Business owner/Managing Director
5. phone number
6. market segment/practise/type

I need a split across the following segments: Tech Managed Services, Trades, Lawyers, Labour hire companies, Construction.

I am looking for a data scraping professional to create an Excel file that contains the database of Malaysia residential property developers from this website:
https://teduh.kpkt.gov.my/senarai-projek-berlesen

The Excel file shall contain the following information in Malay language:
- Developer’s name
- Developer code
- License validity
- Phone Number
- E-mail Address
- Website Address
- Registered Address
- Business Address
- Previous Projects Information
- Project Name
- Project Status
- State
- District
- Price Range

Please refer to the attached sample Excel file.

I need someone to scrape all restaurants in the Netherlands advertising on TheFork.com. For each restaurant, I want to identify which table reservation system they are using on their website. The goal is to gather a complete list of restaurants and map each one to the reservation platform they use. Please share your approach, timeline, and how you will ensure accuracy and completeness.