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Freelance Data Science Startup Jobs (NOW HIRING)

Mindrift

Freelance Data Scraping Engineer (Python)

$37/hr

About the Role This is a freelance role for a Tendem project. As a Python Data Scraping Engineer ... Bachelor's or Master's Degree in Engineering, Applied Mathematics, Computer Science, or related ...

DEUNA

Data Science intern

San Francisco, CA · On-site

About DEUNA DEUNA is a rapidly growing startup revolutionizing global commerce with ATHIA, our AI ... Collaborate with Data Scientists, Data Engineers, and Product teams on ongoing initiatives.

DEUNA

Data Science intern

San Francisco, CA

About DEUNA DEUNA is a rapidly growing startup revolutionizing global commerce with ATHIA, our AI ... Collaborate with Data Scientists, Data Engineers, and Product teams on ongoing initiatives.

Bet365

Data Science Team Lead/Manager

Denver, CO

We are intentionally recruiting for a specific kind of professional: someone with a startup mindset ... Data Science team. Main Responsibilities: • In this hands-on role you will devise, code, and ...

Docugami

Data Science PhD Intern

Kirkland, WA · On-site

You enjoy working at the very cutting edge of R&D * You want to experience an early stage startup ... data science, or math * Experience or strong interest in any of the following: natural language ...

Docugami

Data Science PhD Intern

Kirkland, WA

You enjoy working at the very cutting edge of R&D * You want to experience an early stage startup ... data science, or math * Experience or strong interest in any of the following: natural language ...

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How much do freelance data science startup jobs pay per year?

As of Jul 29, 2026, the average yearly pay for freelance data science startup in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is the difference between Freelance Data Science Startup vs Data Analyst?

AspectFreelance Data Science StartupData Analyst
CredentialsRelevant degrees, certifications in data science or analyticsDegree in statistics, data analysis, or related fields
Work EnvironmentIndependent, project-based, remote or on-siteTypically in corporate or organizational settings, often full-time
Employer & IndustrySelf-employed or startup clients across various industriesEmployers in finance, marketing, healthcare, etc.
Search & Comparison IntentLooking for freelance opportunities or startup roles in data scienceSeeking data analysis roles within organizations

Freelance Data Science Startups focus on independent, project-based work involving advanced data modeling and machine learning, often serving multiple clients. Data Analysts typically work within organizations analyzing data to inform business decisions. While both roles require analytical skills, freelance data science startups emphasize entrepreneurship and technical expertise, whereas data analysts focus on operational data insights within a company.

What is a Freelance Data Science Startup?

A Freelance Data Science Startup is a small business or entrepreneurial venture where individuals or small teams offer data science services independently, rather than working as full-time employees for a single company. These startups provide solutions such as data analysis, machine learning, predictive modeling, and data visualization to various clients on a project basis. Freelance data science startups often work with businesses that need expertise for specific projects or lack in-house data science resources. They may operate remotely and handle multiple clients simultaneously, allowing for flexibility and diverse experience. This model is popular among data scientists seeking autonomy and a variety of challenging projects.

What are some unique challenges freelance data scientists face when working with startups, and how can they effectively manage them?

Freelance data scientists working with startups often encounter challenges such as rapidly changing project scopes, limited historical data, and the need to wear multiple hats. Since startups typically operate in fast-paced environments, priorities can shift quickly, requiring adaptability and strong communication skills. To manage these challenges, it's important to set clear expectations upfront, maintain transparent communication with stakeholders, and design flexible data solutions that can evolve as the business grows. Building strong relationships with both technical and non-technical team members can also help ensure project alignment and successful outcomes.

What are the key skills and qualifications needed to thrive as a Freelance Data Science Startup founder, and why are they important?

To thrive as a Freelance Data Science Startup founder, you need strong expertise in data analysis, machine learning, programming (Python/R), and a solid educational background in statistics or computer science. Familiarity with tools like Jupyter, TensorFlow, cloud platforms (AWS, GCP), and data visualization software, as well as relevant certifications, is highly beneficial. Exceptional communication, client management, and entrepreneurial skills help differentiate successful founders in this space. These skills are crucial for delivering high-quality solutions, winning clients, and sustaining a competitive edge in the evolving data science market.
More about Freelance Data Science Startup jobs
What cities are hiring for Freelance Data Science Startup jobs? Cities with the most Freelance Data Science Startup job openings:
What are the most commonly searched types of Data Science Startup jobs? The most popular types of Data Science Startup jobs are:
What states have the most Freelance Data Science Startup jobs? States with the most job openings for Freelance Data Science Startup jobs include:
What job categories do people searching Freelance Data Science Startup jobs look for? The top searched job categories for Freelance Data Science Startup jobs are:
Freelance Data Science Startup jobs near you
Infographic showing various Freelance Data Science Startup job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 10% Part Time, and 9% Contract. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Freelance Data Scraping Engineer (Python)

Mindrift

New York, NY • On-site, Remote

$37/hr

Part-time

Re-posted 17 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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