Remote Opportunity

Senior Data Scientist - LLM Evaluation (Medhub)

Join EvolutionIQ as a senior professional working remotely from Worldwide. Explore the role, benefits, and apply in one place.

Full Time
$200k - $240k
4 months ago
Worldwide
AI Governance & Programs
Senior
Python
Pandas
SQL
+5 more

Job Description

About Us: EvolutionIQ’s mission is to deliver state of the art technology that helps insurance claims teams make claims handling more accurate, fair, and efficient, so that more people impacted by injury or illness can continue their lives with dignity and stability. We are currently experiencing massive growth and to accomplish our goals, we are hiring world-class talent who want to help build and scale internally, and transform the insurance space. Our team is our #1 priority, and we have been named one of Inc.’s Best Workplaces 3 years in a row and Built In’s Best Places to work in 2025 and 2026! About the Role & You: As a Senior Data Scientist on the Medhub team, you will be the primary architect of our LLM evaluation framework. Think of this role as the "Evaluation Expert" and will define the rigorous statistical standards they must meet before they ever touch production. You believe that LLMs should be held to the same (or higher) scientific standards as traditional supervised models. You enjoy the challenge of turning subjective outputs (like chat and summarization) into objective, measurable data. You are a "Data Scientist’s Data Scientist"—someone who leans heavily into statistical significance, inter-rater reliability, and robust experimental design to ensure our AI products are safe, accurate, and reliable. What You'll Achieve (Performance Outcomes): In this Role You Will: Establish the Gold Standard: Design and implement comprehensive scorecards and benchmarking suites for LLM-based extraction, summarization, and chat interfaces. Bridge the Gap with SMEs: Act as the technical lead in working with Subject Matter Experts (SMEs) to codify their expertise into evaluation datasets and "ground truth" labels. Scale Labeling: Design the statistical guardrails to scale both our human and automated labeling efforts; you will optimize the human labeling process for efficiency and agreement while ensuring LLM-generated labels maintain the highest integrity for our training data. Quantify Risk: Provide clear, data-driven "Go/No-Go" recommendations for model deployment based on rigorous error analysis and statistical confidence intervals. About You (Key Competencies): 5+ years of experience in Data Science with a strong background in traditional statistics (hypothesis testing, experimental design, regression analysis). 2+ years of focused experience working with LLMs, specifically in evaluation, benchmarking, and prompt auditing. Master’s or PhD in Statistics, Mathematics, or a related quantitative field. You should be comfortable explaining the nuances of different evaluation metrics (e.g., G-Eval, ROUGE, or custom-weighted scorecards). A Quality Mindset. You are naturally skeptical of anecdotal evidence ("it looks good") and insist on statistical proof. Proven ability to work with non-technical SMEs to translate their qualitative feedback into quantitative metrics. Proficient in Python (Pandas, Scikit-learn, Statsmodels) and SQL. Familiarity with LLM evaluation frameworks (e.g., RAGAS, LangSmith, or proprietary scorecard systems) is a major plus. Even Better if You Have: Deep knowledge of metrics like Cohen’s Kappa or Fleiss' Kappa to quantify agreement between SMEs and evaluate the clarity of labeling instructions. Experience in Active Learning Experience with platforms like Labelbox, Snorkel, or Prodigy to manage the flow between human annotators and automated systems. Work-life, Culture & Perks: Compensation: The base salary range is $200-240K, with flexibility depending on a candidate’s background and experience. An annual bonus plan and company equity plan (RSUs) are also included in our compensation package. Well-Being: Medical, dental, vision, short & long-term disability, life insurance and AD&D, and 401k matching. Additional family, wellness, and pet benefits. Home & Family: Paid time off and sick leave, 100% paid parental leave (16 weeks for primary caregivers and 12 weeks for secondary caregivers). We offer a flexible schedule for new parents returning to work. Office Life: Catered lunches, happy hours, pet-friendly spaces, and monthly technology stipend. Growth & Training: $1,000/year for each employee for professional development, as well opportunities for tuition reimbursement. Sponsorship: We are open to sponsoring candidates currently in the U.S. who need to transfer their active visa. Please check with our Recruiting team if your visa is applicable for transfer. EvolutionIQ appreciates your interest in our company as a place of employment. EvolutionIQ is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Requirements

  • 5+ years of experience in Data Science with a strong background in traditional statistics (hypothesis testing, experimental design, regression analysis).
  • 2+ years of focused experience working with LLMs, specifically in evaluation, benchmarking, and prompt auditing.
  • Master’s or PhD in Statistics, Mathematics, or a related quantitative field.
  • A Quality Mindset. You are naturally skeptical of anecdotal evidence ('it looks good') and insist on statistical proof.
  • Proven ability to work with non-technical SMEs to translate their qualitative feedback into quantitative metrics.
  • Proficient in Python (Pandas, Scikit-learn, Statsmodels) and SQL.
  • Familiarity with LLMs and their evaluation metrics.

Benefits

  • 401k Matching
  • Certification Support
  • Flexible Hours
  • Gym Membership
  • Health Insurance
  • Home Office Budget
  • Learning Budget
  • Paid Time Off

Skills

Python
Pandas
SQL
LLMs
Scikit-learn
Statsmodels
G-Eval
ROUGE

Ready to Apply?

Join EvolutionIQ today

Salary Range
$200k - $240k
Posted 4 months ago

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