Extracción de datos Jobs

I need a robust predictive model that flags customers at risk of churning based solely on the categorical variables we collect in our CRM. The raw data are already exported to CSV—things like plan type, signup channel, region, and support-ticket categories—but they have never been cleaned or engineered for modelling. Here is what I want to walk away with: • A fully reproducible pipeline (Python preferred, using pandas, scikit-learn or equivalent) that: – ingests the categorical dataset, – performs sensible encoding and imbalance handling, – trains several candidate algorithms, – selects the best performer through cross-validation, and – outputs calibrated churn probabilities for each record. • A validation report...

I need an experienced data-gathering developer to assemble a clean, well-structured database of roughly 100,000 companies pulled from Yellow Pages and Google My Business. You may also enrich the list with any reputable open databases that fit the brief. The finished file must arrive as a single, comma-separated CSV ready for import into my CRM. Each row should include: • Company name • Industry / business sector • State / region • City • ZIP / postal code • Email address • WhatsApp number • Phone number(s) • Website URL I’m counting on automated verification tools to weed out duplicates, flag invalid emails and phone numbers, and generally keep the error rate to an absolute minimum. Scraping scripts built with Python (...

Procedure: 1 – Review the document and check address. 2 – Take 7-8 Geotagged site visit pictures of the IA with different angles (Gate and Signage of the IA must be visible) 3 – Submit the documents to the relevant person (HR/Admin/Exam depart/HOD/Receptionist/Owner/Head/Manager etc.) 4 – Ask the verifier to provide us verification by filling out the form or if they refuse ask them to provide us verification on official letter head or as per the institute’s policy. 5 – Note down the Verifier Details and ask for business card. 6 – Fill out the Site visit form. 7 - Written/Recorded Refusal statement in case of refusal.

Need Web based crawling documents for English Document sourcing from US based, Single paged document with 300 word, need 30% of equations with available sourced link. for the below domains Academicpapers, Text books, Exam papersand problemsets, Scientific journals, Technical manuals, Patent filings, Lecture notes.

We need a freelancer to: 1. extract target procurement line items from Spanish documents; The number of documents are 20 pdfs. 2. clean and normalize descriptions, quantities, units, brands, models, and technical attributes; 3. identify comparable supplier products using the approved source environment; 4. extract prices, currencies, package sizes, and source information; 5. convert prices into standardized unit prices; 6. flag uncertain matches and cases where no reliable match is available; 7. submit a reproducible data file and workflow documentation. Deliverables are: • : one row per procurement item and candidate supplier match; • : a machine-readable version of the same data; • , , or equivalent reproducible workflow, when automation is used. (You are free ...

Procedure: 1 – Review the document and check address. 2 – Take 7-8 Geotagged site visit pictures of the IA with different angles (Gate and Signage of the IA must be visible) 3 – Submit the documents to the relevant person (HR/Admin/Exam depart/HOD/Receptionist/Owner/Head/Manager etc.) 4 – Ask the verifier to provide us verification by filling out the form or if they refuse ask them to provide us verification on official letter head or as per the institute’s policy. 5 – Note down the Verifier Details and ask for business card. 6 – Fill out the Site visit form. 7 - Written/Recorded Refusal statement in case of refusal.

Procedure: 1 – Review the document and check address. 2 – Take 7-8 Geotagged site visit pictures of the IA with different angles (Gate and Signage of the IA must be visible) 3 – Submit the documents to the relevant person (HR/Admin/Exam depart/HOD/Receptionist/Owner/Head/Manager etc.) 4 – Ask the verifier to provide us verification by filling out the form or if they refuse ask them to provide us verification on official letter head or as per the institute’s policy. 5 – Note down the Verifier Details and ask for business card. 6 – Fill out the Site visit form. 7 - Written/Recorded Refusal statement in case of refusal.

My full-stack web-scraping and data-extraction platform is ready for real-world scrutiny before its public release. I need fresh eyes to confirm two critical points: that pages load and jobs run quickly under normal and heavy loads, and that the data pulled from websites, APIs, and databases is consistently accurate. Because the platform is designed for both technical and non-technical operators, I want feedback from testers who represent each group. You might dive into advanced settings, schedule complex crawls, or simply walk through the no-code workflow—either way, your impressions matter. Here’s how I see the collaboration working: • You will create or use existing scraping tasks for websites, APIs, and relational databases, then note any slowdowns, bottlenecks, or ...

I need the current probate filings for Harris, Travis, and Williamson counties in Texas systematically investigated and scraped so I can pinpoint estates where the property owner lived in Texas but the heirs now reside elsewhere. The end goal is a clean spreadsheet that lets me reach those out-of-state heirs, discuss their financial interest, and step into their place in the probate process. Scope of work • Locate every active probate case in the three counties. • Capture heirs’ contact details (names, mailing addresses, phone/email when available), the associated property details (street address, parcel/lot, assessed value if posted), and the present case status. • Verify that at least one heir’s address is outside Texas or flag the record if residency is...

I need solid, verifiable information on the OzBargain member or members who actually publish the discounted-product deals. Your task is to search the site—manually, with a custom scraper, or any other ethical data-gathering method you prefer—and hand back clear evidence of who is behind the posts. Please return: • Username or profile ID exactly as it appears on OzBargain • Total number of deals that account has posted to date (screenshots or direct links for proof) • Current reputation / karma score shown on the profile A concise spreadsheet or Google Sheet is perfect, as long as every data point links back to its original page for easy verification.

I need a single CSV that holds around 14 million company profiles compiled from publicly available sources. Each record has to include, at minimum, the following columns: • Company name • business sector (ex. real estate, pharmaceutical industry, chemical sector, education, etc) • WhatsApp • Telephone • Email • Web site • State • City Accuracy and freshness are critical; I will run random spot-checks on the contact data before final acceptance. You may use any reliable mix of web scraping, public registries, APIs, or existing datasets—as long as licensing permits commercial use. Please outline your data-gathering approach, expected turnaround time, and any staging you need for such a large volume. The final delivery must be a ...

Title: Find 2 Decision-Maker Contacts for 500 Shopify Ecommerce Brands I need a lead researcher to find up to TWO relevant decision-makers per company for 500 Shopify ecommerce brands. I will provide a spreadsheet with company name, website, and LinkedIn company URL. Your task is to find the best contacts for ecommerce operations, payments, chargebacks, refunds, customer experience, risk, or finance. Best titles to look for: Founder Co-Founder CEO COO President Owner Head of Operations Director of Operations VP Operations CFO Finance Director Payments Manager Risk Manager Fraud Manager Do not return marketing, social media, PR, designer, sales, retail store, warehouse, influencer, or junior contacts unless there is no better option. Required output columns only: Company Name Contac...

Each month I need fresh consumer-listing data pulled from both and YellowPages.ca. The focus is on contact information only, specifically the name, full mailing address, and phone number that appear on each record. Here’s how I picture the workflow: • You run an automated scrape on the two sites, bypassing basic anti-bot measures without overloading their servers. • You clean and deduplicate the results so every row represents a unique listing. • You deliver a single, well-structured CSV file (UTF-8) containing three columns: Name, Address, Phone. I’m open to the toolset you prefer—Python, Scrapy, Selenium, or an equivalent stack—as long as the output remains consistent month after month. If you have an existing script that can be adapted, gre...

I'm conducting research on trading software and need a skilled survey researcher to gather responses from professional stock traders in North America. Key Requirements: - Target Audience: Professional stock traders - Geographic Focus: North America - Purpose: Research questions on trading software Ideal Skills and Experience: - Experience in sourcing and engaging survey respondents - Network or database of professional traders - Familiarity with the stock market and trading software - Ability to ensure a diverse and representative respondent pool Please provide a detailed plan on how you would approach this task, including any relevant experience.

I need contact details scraped from 1-2 matrimony sites for my matrimony venture. Requirements: - Experience in web scraping - Familiarity with matrimony sites - Ability to deliver data in organized format Ideal Skills: - Proficient in Python or similar languages - Knowledge of scraping tools like BeautifulSoup or Scrapy - Attention to detail and data accuracy Please provide samples of previous work and estimated delivery time.

I need contact details scraped from 1-2 matrimony sites for my matrimony venture. Requirements: - Experience in web scraping - Familiarity with matrimony sites - Ability to deliver data in organized format Ideal Skills: - Proficient in Python or similar languages - Knowledge of scraping tools like BeautifulSoup or Scrapy - Attention to detail and data accuracy Please provide samples of previous work and estimated delivery time.

I need the current probate filings for Harris, Travis, and Williamson counties in Texas systematically investigated and scraped so I can pinpoint estates where the property owner lived in Texas but the heirs now reside elsewhere. The end goal is a clean spreadsheet that lets me reach those out-of-state heirs, discuss their financial interest, and step into their place in the probate process. Scope of work • Locate every active probate case in the three counties. • Capture heirs’ contact details (names, mailing addresses, phone/email when available), the associated property details (street address, parcel/lot, assessed value if posted), and the present case status. • Verify that at least one heir’s address is outside Texas or flag the record if residency is...

I have a curated dataset of patients’ genetic profiles and need a deep-learning solution that can reliably flag the presence of heart disease. Because the data are entirely genomic, the job begins with thoughtful preprocessing and feature engineering (handling high-dimensional SNPs, normalisation, train/validation split, class-imbalance techniques if required). My single, overriding success metric is F1 Score; accuracy alone will not do, so the model must be tuned to balance precision and recall. You may choose the exact framework—PyTorch or TensorFlow/Keras are both fine—as long as the final code is clean, reproducible, and GPU-ready. Deliverables • End-to-end Python code or notebook that loads the raw genetic data, performs preprocessing, trains the deep neur...

I am looking for an automated bot for "Pocket Option" to handle only the Martingale (2X) trades under specific conditions: Trading Rules: 1. The bot will take over only after my first trade results in a loss. 2. It will execute a 2X Martingale (double the trade size) only for the next trade of the specific chart where the loss occurred. 3. Martingale is not allowed if: - A Doji candle appears. - The loss is caused by gap-up or gap-down conditions. - The entry was taken late. 4. Each chart/setup must have independent Martingale management (no combination of trades across charts). 5. Only one 2X Martingale level is permitted per trade sequence — no further progression. Specifics: - No need for notifications. - Real-time execution for Pocket Option platform. Budget...

I need the current probate filings for Harris, Travis, and Williamson counties in Texas systematically investigated and scraped so I can pinpoint estates where the property owner lived in Texas but the heirs now reside elsewhere. The end goal is a clean spreadsheet that lets me reach those out-of-state heirs, discuss their financial interest, and step into their place in the probate process. Scope of work • Locate every active probate case in the three counties. • Capture heirs’ contact details (names, mailing addresses, phone/email when available), the associated property details (street address, parcel/lot, assessed value if posted), and the present case status. • Verify that at least one heir’s address is outside Texas or flag the record if residency is...

I'm working on a master's project and need help with statistical analysis using SPSS. Key areas where I need assistance: - Descriptive statistics: mean, median, mode, standard deviation, and variance. - Data visualization: creating charts and graphs. Ideal skills and experience: - Proficiency in SPSS - Strong background in statistics - Experience with data visualization techniques

I need a reliable data-scraper who can pull clean, non-spam-flagged email addresses for companies in my local market. All addresses should be sourced directly from company websites, their social media profiles, and reputable business directories—nothing scraped from questionable lists. Please structure the results in a single Excel spreadsheet so my team can sort and filter with ease. At minimum, every row must include a working email address; if you happen to capture basic contact details (company name, phone, street address) while you work, feel free to include those in adjacent columns, but the email is the critical field. Before delivery, validate each address to avoid hard bounces or obvious spam traps. Any toolset is fine—Python, Scrapy, Hunter, NeverBounce, or simi...

I need a web scraper / data extraction to collect structured business data for all Supermarkets and Hypermarkets listed on across the UAE. --- **Data Fields Required:** - Business Name - Contact Number (Landline) - Mobile Number - Email Address - Full Address - Emirate (Dubai, Abu Dhabi, Sharjah, Ajman, Ras Al Khaimah, Fujairah, Umm Al Quwain) - Website URL - Business Category / Sub-category (e.g. Supermarket, Hypermarket, Mini Mart) - Social Media Handles (if listed – Instagram, Facebook, WhatsApp) --- **Deliverable:** - Clean, deduplicated data in Excel (.xlsx) and CSV format - One row per business location (not per brand) - Separate column for each emirate for easy filtering - No blank/junk rows; all columns properly labeled --- **Requirements:** - Proven experience scrapin...

I have a curated dataset of patients’ genetic profiles and need a deep-learning solution that can reliably flag the presence of heart disease. Because the data are entirely genomic, the job begins with thoughtful preprocessing and feature engineering (handling high-dimensional SNPs, normalisation, train/validation split, class-imbalance techniques if required). My single, overriding success metric is F1 Score; accuracy alone will not do, so the model must be tuned to balance precision and recall. You may choose the exact framework—PyTorch or TensorFlow/Keras are both fine—as long as the final code is clean, reproducible, and GPU-ready. Deliverables • End-to-end Python code or notebook that loads the raw genetic data, performs preprocessing, trains the deep neur...

I need comprehensive contact data of retail sector businesses in Pakistan planning to expand to South Punjab, specifically Multan. This includes: - Email addresses - Cell numbers - WhatsApp numbers - LinkedIn accounts - Official phone numbers Ideal Skills and Experience: - Experience in data mining and lead generation - Familiarity with the retail sector in Pakistan - Ability to deliver accurate and verified information quickly Please include detailed project proposals in your application.

I’m assembling a sizeable AI training dataset focused exclusively on first-person recordings of manufacturing processes. All footage must be shot from an egocentric point of view—helmet cam, chest rig, or smart-glasses—so the viewer sees exactly what the worker sees while performing hands-on tasks on the factory floor. Scope • Subject matter: professional, manual-labor environments only; think assembly lines, machine operation, quality checks, packaging, tool handling, and similar day-to-day manufacturing actions. • Volume: I will need a large number of distinct clips, captured in varied settings, lighting conditions, and with different operators to maximise data diversity. • Quality: full-HD or higher, steady perspective, clear visibility of hands, tools,...

I need the top 1000 contact email addresses for each category: 1. Every country in the world's main contact email. Around 5 emails per country. 2. Every country in the world's intelligence service. 3. Every country in the world's military service. 4. Top 1000 wealthiest global families. 5. All global royal families. 6. 1000 of the world's top diplomats and dignitaries. 7. Top 1000 wealthiest individuals. 8. Top 1000 female Christian religious scholars globally. 9. Top 1000 global human rights groups. 10. Top 1000 International Criminal Courts contact emails. 11. Top 1000 Interpol contact emails. Thank you for your time. I look forward to your work.

I’m looking for an experienced web-scraping specialist to capture detailed product information. The target sites are e-commerce and marketplace style domains; I’ll share the exact URLs once we’ve agreed to proceed.

Hiring a data scraping expert proficient in Python. In addition to extract, should provide source code as well. Key Requirements: - Extensive experience in data scraping USA websites. - Previous experience in overcoming anti-scraping mechanisms. - Proficiency in Python and understanding of its libraries for web scraping. - Familiarity with paid proxies and can effectively utilize them.

Hello, I am sharing couple of sites which I need mainly, but if you have similar type of site please share the pricing and your publishing charges. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

I need a freelancer to create a comprehensive database of publicly available contact information for a specified list of names. The database should include: - Email addresses - Phone numbers - Mailing addresses - Titles and assistants - Work and home addresses - Instagram profiles Ideal skills and experience: - Experience in data collection and database creation - Familiarity with public data sources - Attention to detail and accuracy - Proficiency in using data management tools - filling out the following Salutation FirstName MiddleInitial LastName Nickname Suffix Title Company EmailAddress1 EmailAddress2 BusinessPhone MobilePhone HomePhone BusinessFax AssistantFirstName AssistantLastName AssistantEmail Assistantemail2 AssistantPhone BusinessAddressLine1 BusinessAddressLine2 BusinessCi...

I need a clean, accurate database of 30,000 Australia-based executives. C-suite roles are the priority, but I’m open to a healthy mix of senior decision-makers if that helps reach the target count without sacrificing data quality. The list must be delivered in CSV or Excel and include, at minimum, each executive’s name, job title, company, direct email, direct phone (mobile or direct line preferred), and a working LinkedIn profile URL. I will spot-check the file, so a bounce rate under 5 % is essential and generic addresses (info@, admin@, etc.) will be rejected. You are free to pull from any reliable source—LinkedIn Sales Navigator, ZoomInfo, company websites, industry directories, or verified web scraping—so long as the information is recent and complies with A...

Hi, We're looking for web scraping specialists or data engineers who extract data, whether at small scale or at scale on behalf of clients, to evaluate a new tool that's currently live. Freelancers we've shown it to are cutting scraping time by 3x or more and saving over 90% on LLM token costs at scale, with no AI hallucinations, taking on far more clients without the extra overhead. We're looking for freelancers to test it, share feedback, and see if it can have the same impact for you. A 15 minutes call is all we need. Thanks!

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 reg...

PROFESSIONAL SUMMARY Detail-oriented and systems-focused Data Specialist specializing in end-to-end data pipelines for remote business environments. Proven expertise in taking raw, fragmented business datasets and transforming them into structured, automated, and visually striking Power BI dashboards and Excel models. Expert in data cleansing, relational data modeling, and advanced business intelligence analytics (DAX, Power Query, XLOOKUP, and Pivot Tables) aimed at helping remote teams optimize operations, increase sales performance, and make data-driven decisions. TECHNICAL SKILLS MATRIX Data Analysis & BI: Power BI Desktop, Power BI Service, Power Pivot, Data Modeling (Star Schema), DAX (Data Analysis Expressions) Measures. Advanced Spreadsheet Engineering: Microsoft Excel, Googl...

PROFESSIONAL SUMMARY Detail-oriented and systems-focused Data Specialist specializing in end-to-end data pipelines for remote business environments. Proven expertise in taking raw, fragmented business datasets and transforming them into structured, automated, and visually striking Power BI dashboards and Excel models. Expert in data cleansing, relational data modeling, and advanced business intelligence analytics (DAX, Power Query, XLOOKUP, and Pivot Tables) aimed at helping remote teams optimize operations, increase sales performance, and make data-driven decisions. TECHNICAL SKILLS MATRIX Data Analysis & BI: Power BI Desktop, Power BI Service, Power Pivot, Data Modeling (Star Schema), DAX (Data Analysis Expressions) Measures. Advanced Spreadsheet Engineering: Microsoft Excel, Googl...

Mais detalhes: Which platforms will the Aviator predictor be used on? Mobile, Web What functionality do you need in the Aviator predictor? Real-time predictions, Historical data analysis How will the data be sourced for the Aviator predictor? Manual data input