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Data Scraping Jobs in New York (NOW HIRING)

MLabs

Web Scraping Specialist

New York, NY · On-site +1

$75K - $100K/yr

Data Retrieval: Manage complex data retrieval tasks, including handling pagination and dynamic ... Regularly monitor scraping processes and infrastructure to identify and resolve issues, ensuring a ...

MLabs

Web Scraping Specialist

New York, NY · Remote

$75K - $100K/yr

Data Retrieval: Manage complex data retrieval tasks, including handling pagination and dynamic ... Regularly monitor scraping processes and infrastructure to identify and resolve issues, ensuring a ...

Understood

Senior Research Manager - Product & AI

New York, NY · On-site

$138K - $182K/yr

Own the "always-on" scraping and updating of product landscapes to ensure Understood remains ahead of market trends * Design and maintain AI bots (e.g. Gemini GEMs) to create automated data pipelines ...

Hebbia

Applied Research Engineer, Agents

Manhattan, NY · On-site

$225K/yr

... data scraping techniques • Prior experience in developing NLP models and systems • Excellent problem-solving and analytical skills • Strong communication and teamwork abilities • Strong ...

Melotech

Data Science, Music & Audio

New York, NY · On-site

Discovering and exploiting new, untapped data sources through creative scraping techniques * Building data processing pipelines from scratch to handle raw, unstructured data * Using LLMs and agentic ...

SysMind Tech

Data Engineer

Manhattan, NY · On-site

$126K - $151K/yr

Role: Data Engineer Location- New York, NY JD- Must have finance (investment/capital markets ... Experience with web-scraping. Strong problem-solving skills and the ability to work independently ...

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Data Scraping information

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How much do data scraping jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for data scraping in New York is $32.61, according to ZipRecruiter salary data. Most workers in this role earn between $20.76 and $39.95 per hour, depending on experience, location, and employer.

What are the typical challenges faced in data scraping, and how are they addressed?

Data Scraping professionals often encounter challenges such as dealing with anti-scraping measures, frequent changes to website structures, and managing large volumes of unstructured data. These obstacles require adaptability and creative problem-solving, as well as continuous learning to update scripts and leverage the latest tools. Team collaboration is common—data scrapers may work closely with data analysts, engineers, or business stakeholders to ensure the data collected meets the project's needs. Proactively communicating and staying current with industry best practices helps data scraping specialists efficiently navigate these challenges and deliver high-quality results.

What is a data scraping?

A Data Scraping job involves extracting structured data from websites or online sources using automated tools or scripts. This data is then used for various purposes, such as market research, competitive analysis, or business intelligence. Professionals in this field typically use programming languages like Python or tools like Scrapy and BeautifulSoup to collect and organize data efficiently. However, ethical considerations and legal guidelines must be followed to ensure compliance with website policies and data protection laws.

What are the key skills and qualifications needed to thrive in data scraping, and why are they important?

To excel in Data Scraping, proficiency in programming languages such as Python or JavaScript, familiarity with web protocols, and understanding of data extraction methodologies are essential, often supported by a degree in computer science or a related field. Experience with web scraping tools like BeautifulSoup, Scrapy, or Selenium, and knowledge of APIs are commonly required; relevant certifications in data analysis or automation can be advantageous. Strong problem-solving skills, attention to detail, and effective communication help professionals successfully tackle complex data challenges and collaborate with teams. These competencies are vital to reliably gather, process, and deliver valuable data while adhering to legal and ethical standards.

What are the most commonly searched types of Data Scraping jobs in New York? The most popular types of Data Scraping jobs in New York are:
What are popular job titles related to Data Scraping jobs in New York? For Data Scraping jobs in New York, the most frequently searched job titles are:
What job categories do people searching Data Scraping jobs in New York look for? The top searched job categories for Data Scraping jobs in New York are:
Data Scraping jobs near you
Infographic showing various Data Scraping job openings in New York as of August 2026, with employment types broken down into 72% Full Time, 14% Part Time, and 14% Contract. Highlights an 100% In-person job distribution, with an average salary of $67,832 per year, or $32.6 per hour.

Freelance Data Scraping Engineer (Python)

Mindrift

New York, NY • Remote

$37/hr

Part-time

Re-posted 26 days ago

Job description

Mindrift is looking for highly skilled Web Scraping specialists to join the Tendem project (https://tendem.ai/) and drive specialized data scraping workflows for real-world use cases.

Mindrift is looking for highly skilled Python Data Scraping Engineers to join the Tendem project and drive specialized data scraping workflows for real-world applications.

In this role, you'll apply your expertise in web scraping, data extraction, and data processing to deliver accurate, reliable, and high-quality results. This part-time remote opportunity is ideal for technical professionals with hands-on experience in web scraping, data extraction, and processing.

What We Do 

The Mindrift platform connects specialists with innovative technology projects. Our mission is to help develop high-quality AI technologies by combining real-world expertise from professionals across the globe with advanced AI development efforts.

About the Role

This is a freelance role for a Tendem project. As a Python Data Scraping Engineer, you'll handle data scraping tasks requiring technical precision for web extraction and processing, utilizing tools such as Apify, OpenRouter, and other technologies, alongside your own technical expertise and approaches. 

Key Responsibilities

  • Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.
  • Leverage available tools and custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements.
  • Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior.
  • Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery.
  • Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.

Educational qualifications

  • At least 3+ years of relevant experience in data engineering, web scraping, automation, or software development (required).
  • Bachelor's or Master's Degree in Engineering, Applied Mathematics, Computer Science, or related technical fields is a plus.

Academic and/or Professional Experience

Candidates should have a strong technical foundation and practical experience with scripting, automation, and data extraction workflows. We are looking for specialists who can solve non-trivial problems, work confidently with modern web technologies and data processing tools, and systematically collect, structure, and validate data from diverse sources. A methodical, detail-oriented approach and the ability to work independently are essential.

Technical Skills (Essential)

  • Strong experience in Python web scraping (BeautifulSoup, Selenium or similar), including dynamic content (JS, AJAX, infinite scroll) and APIs via proxies
  • Proven ability to extract data from complex structures (hierarchies, archived pages, inconsistent HTML)
  • Solid background in data cleaning, normalization, and validation, delivering structured datasets (CSV, JSON, Google Sheets)

Additional requirements

  • Hands-on experience with LLMs and AI frameworks to enhance automation and problem-solving
  • Strong attention to detail and commitment to data accuracy
  • Self-directed work ethic with ability to troubleshoot independently
  • A link to GitHub is a plus
  • English proficiency: Upper-intermediate (B2) or above (required)

Project time expectations 

For this project, tasks are estimated to require around 10-20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.

Compensation 

On this project, contributors can earn up to $37 per hour equivalent, depending on their level and pace of contribution.

Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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