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Freelance Data Science Startup Jobs (NOW HIRING)

... startup environment. Program Details: Evolver is launching a small, highly selective summer internship cohort for students and emerging talent to gain hands-on experience applying data science ...

Data Science Team Leader

Denver, CO ยท On-site

$155K - $165K/yr

As the Data Science Team Leader, you will be a critical part of our expanding global data ... We are intentionally recruiting for a specific kind of professional: someone with a startup mindset ...

As the Data Science Team Leader, you will be a critical part of our expanding global data ... We are intentionally recruiting for a specific kind of professional: someone with a startup mindset ...

Data Science Team Leader

Denver, CO ยท On-site

$155K - $165K/yr

As the Data Science Team Leader, you will be a critical part of our expanding global data ... Provenexperience working in a fast-paced, agile, or startup-like environment. You must have a ...

Director of Data Science

Mountain View, CA ยท On-site

$174K - $299K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are proud to have the best of both worlds - a startup culture with the resources of a large ... Role Overview Coupang is seeking a Director of Data Science to lead high-impact, data-driven ...

Director of Data Science

Mountain View, CA ยท On-site

$174K - $299K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are proud to have the best of both worlds - a startup culture with the resources of a large ... Role Overview Coupang is seeking a Director of Data Science to lead high-impact, data-driven ...

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Freelance Data Science Startup information

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$37.5K

$122.7K

$196.5K

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

As of Aug 19, 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 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 skills and qualifications are needed to thrive as a freelance data science startup founder?

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.

What unique challenges do freelance data scientists face when working with startups, and how can they 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 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.

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?

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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:

Infographic showing various Freelance Data Science Startup job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Applied Data Science Intern

Evolver

Palo Alto, CA โ€ข On-site

Full-time, Internship

Re-posted 16 hours ago


Job description

Applied Data Science Summer Internshipย 

About Us:

Evolver is a rapidly growing enterprise AI company building advanced solutions for Fortune 500 organizations across finance, tax, risk, and audit. In just 1.5 years, the company has grown from 0 to nearly 100 employees, bringing together an exceptional team of technologists, researchers, and industry experts. Founders includes former executives from some of the world's top organizations, including the former Global CTO and Global Board Member of Ernst and Young and the former VP of AI from Microsoft, alongside senior leaders from other major global enterprises. The team includes multiple PhDs and a strong concentration of employees with advanced degrees from leading universities. This in-person internship offers a small cohort of students the opportunity to work directly alongside experienced operators and AI experts while gaining hands-on exposure to using the latest innovations in data science applications at a frontier startup environment.

Program Details:

Evolver is launching a small, highly selective summer internship cohort for students and emerging talent to gain hands-on experience applying data science techniques to enterprise datasets while learning to leverage and deploy AI systems for real-world Fortune 500 business use cases.

This is an intensive 10-week, full-time small cohort program designed to provide direct mentorship from experienced professionals in computer science, data science, artificial intelligence, and enterprise software deployment.

  • Duration:ย 10 weeks (full-time), June through Early August.
  • Competitive Compensation:ย Tailored to your experience and skill set.
  • Format:ย Hybrid (4+ days in person) - Based in Palo Alto, CA off University Ave
  • Cohort Size:ย Small and mentorship-focused
  • Learning Goals: Develop and apply AI-driven data science solutions on real-world datasets and workflows supporting Fortune 500 enterprise use cases.

Role Details:

Interns will contribute to real data innovation projects involving:

  • Data analysis and machine learning pipelines
  • AI agents, retrieval systems, and evaluation frameworks
  • Enterprise AI integration and deployment tooling
  • Product prototyping and applied research
  • Automation systems for large-scale organizational use
  • Real world enterprise use cases of graph theory
  • Gain direct exposure to Fortune 500 clients
  • Access enterprise-scale AI and data science initiatives through hands-on collaboration with internal teams and customer engagements.

Projects are oriented toward practical AI solutions deployed in enterprise and Fortune 500 environments.

Mentorship & Learning

Interns will work closely with experienced staff and technical mentors with expertise in:

  • Computer Science
  • Data Science & Analytics
  • Applied AI & Machine Learning
  • Enterprise Infrastructure
  • Scalable AI Deployment
  • Risk and Compliance Frameworks
  • Tax and Audit

The program is structured as a high-engagement cohort-based apprenticeship experience emphasizing:

  • Daily in person technical collaboration
  • Rapid learning and iteration
  • Exposure to real deployment challenges
  • Cross-disciplinary problem solving
  • Professional development in AI engineering and enterprise systems

Who Should Apply:

We welcome applications from:

  • Graduate students with a record of excellence
  • Exceptional advanced undergraduates

All candidates are required to be recommended by an accredited professor leading a relevant program at a top university. Will be verified during application process.

Strong candidates typically demonstrate:

  • Programming experience
  • Curiosity about AI systems and emerging technologies
  • Initiative, creativity, and strong problem-solving ability
  • Prior technical, research, or project experience

You do not need deep expertise in every area, we value intellectual curiosity, adaptability, and motivation to build.