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Senior Data Scientist (Insurance Claims)

Role overview

Qualifications

  • 4-7 years in Data Science with a strong track record of deploying models into production environments.
  • Deep experience with casualty claims, including at least 4 years of hands-on work in Workers’ Compensation or General Liability.
  • Strong proficiency in Python and solid software engineering fundamentals.
  • Expertise in unsupervised learning techniques and NLP methods for analyzing complex, unstructured data.

Responsibilities

  • Design and own the mathematical and technical framework for a scalable clustering engine.
  • Partner with Machine Learning Engineers to translate prototypes into optimized production systems.
  • Collaborate with Data and Application Engineering teams to define APIs and data contracts.
  • Develop advanced representations of claims using both structured and unstructured data.

About the company

CLARA Analytics logo

CLARA Analytics

Company details

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Job description

About CLARA Analytics

CLARA Analytics is the leading AI as a service (AIaaS) provider that improves casualty claims outcomes for commercial insurance carriers and self-insured organizations. The company’s product suite for workers comp, commercial auto and general liability insurance claims applies image recognition, natural language processing, and other AI-based techniques to unlock insights from medical notes, bills and other documents surrounding a claim. CLARA’s customers include companies from the top 25 global insurance carriers to large third-party administrators and self-insured organizations. Founded in 2017, CLARA Analytics is headquartered in California’s Silicon Valley. For more information, visit www.claraanalytics.com.



About the role

We’re seeking a Senior Data Scientist to architect and lead the development of our core Claim Clustering Platform—the intelligence layer that powers how we compare and analyze Bodily Injury (BI) claims across Workers’ Compensation, General Liability, and Auto Liability. This is a highly technical, hands-on role where you will design systems that move beyond experimentation into robust, production-grade solutions. You’ll collaborate closely with Machine Learning Engineers and MLOps specialists to ensure scalability, reliability, and continuous improvement. You’ll also serve as a critical bridge to Data and Application Engineering teams, ensuring seamless integration with downstream systems such as benchmarking and fraud detection.



What You'll Do

  • Design and own the mathematical and technical framework for a scalable clustering engine that groups claims based on clinical, legal, and financial attributes.
  • Partner with Machine Learning Engineers to translate prototypes into optimized production systems, and work with MLOps to implement automated retraining, monitoring, and model lifecycle management.
  • Collaborate with Data and Application Engineering teams to define APIs and data contracts that power internal tools such as attorney and physician benchmarking, as well as fraud detection systems.
  • Develop advanced representations of claims using both structured data (e.g., ICD codes, geographic data, indemnity and legal costs) and unstructured data (e.g., adjuster notes, medical records, legal documents).
  • Act as a subject matter expert within the broader engineering organization, ensuring alignment between data science initiatives, system architecture, and production reliability standards.



What We’re Looking For

  • 4-7 years in Data Science with a strong track record of deploying models into production environments.
  • Deep experience with casualty claims, including at least 4 years of hands-on work in Workers’ Compensation or General Liability. Familiarity with claim lifecycles, medical billing (ICD/CPT), litigation processes, and reserve dynamics is crucial.
  • Strong proficiency in Python and solid software engineering fundamentals, including system design, CI/CD pipelines, and API development/versioning.
  • Expertise in unsupervised learning techniques (clustering, dimensionality reduction) and NLP methods (transformers, embeddings, LLM-based approaches) for analyzing complex, unstructured data.
  • Proven ability to lead and execute projects across Data Science, Engineering, DevOps, and Product teams.



What We Offer

  • The opportunity to make a real impact on a growing company.
  • Collaborative and supportive work environment.
  • Competitive compensation package.
    • Salary + Bonus
    • Benefits: generously subsidized health insurance, employer-paid ancillary benefits, flex/unlimited PTO, fully remote, 401k with company match
  • Be a part of a team that is passionate about what we do!

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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