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Freelance Data Science Startup Jobs in Indiana (NOW HIRING)

Alignerr

Principal Clinical Scientist

Indianapolis, IN · Remote

... science could directly shape how AI understands and reasons about medical evidence? We're looking ... Deep expertise interpreting clinical data for agencies such as the FDA, EMA, or equivalent global ...

Cheez

Product Manager @ Social app startup

Gary, IN

Bachelor's degree in Computer Science, Engineering, Business or a related field (preferred, not ... Strong analytical and critical thinking abilities, with a data-driven approach to decision-making

Lilly

Associate Director Data and Systems QA

Lebanon, IN · On-site

$123K - $180.40K/yr

This is a unique opportunity to be a part of the team for the startup of a greenfield manufacturing ... Basic Requirements: * BS or higher degree in Engineering/Science, Computer Science, Information ...

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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.

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 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 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.

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Principal Clinical Scientist

Alignerr

Indianapolis, IN • Remote

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Principal Clinical Scientist (AI Training)
About the Role
What if your career-long expertise in clinical trial design and regulatory science could directly shape how AI understands and reasons about medical evidence? We're looking for a Principal Clinical Scientist to bring senior-level rigor to frontier AI research - ensuring the clinical data and analyses powering next-generation AI systems meet the same exacting standards expected in real-world regulatory submissions.
This is a fully remote, flexible contract role built for experienced clinical scientists who want to contribute to something genuinely new. No AI background required - just deep command of clinical research and a sharp eye for scientific quality.
  • Organization
    : Alignerr
  • Type
    : Hourly Contract
  • Location
    : Remote
  • Commitment
    : 10-40 hours/week
    • What You'll Do
    • Design and critically review clinical trial protocols used to generate high-quality, regulatory-grade datasets for AI training
    • Interpret and audit clinical trial results for accuracy, consistency, and alignment with regulatory expectations
    • Evaluate AI-generated clinical analyses for scientific soundness and methodological integrity
    • Provide structured expert feedback that directly improves how AI models reason about clinical evidence, outcomes, and trial data
    • Work independently and asynchronously - fully on your own schedule
    Who You Are
    • Senior-level experience designing clinical trial protocols intended for regulatory submission
    • Deep expertise interpreting clinical data for agencies such as the FDA, EMA, or equivalent global bodies
    • Strong grounding in clinical research methodology, biostatistics, or translational science
    • Naturally detail-oriented with a rigorous, systematic approach to evaluating scientific quality
    • Clear and precise written communicator - able to document findings and feedback with authority
    • No prior AI or tech experience required
    Nice to Have
    • Prior involvement in data annotation, data quality assurance, or evaluation systems
    • Experience reviewing or contributing to clinical evidence packages for drug, device, or diagnostic submissions
    • Background spanning multiple therapeutic areas or trial phases
    • Familiarity with AI-generated content or model evaluation workflows
    Why Join Us
    • Work directly on frontier AI systems with real impact on clinical and biomedical research
    • Fully remote and flexible - work when and where it suits you
    • Freelance autonomy with the structure of meaningful, expert-level work
    • Influence how AI understands, evaluates, and communicates real-world clinical evidence
    • Potential for ongoing work and contract extension as new projects launch

Apply