Staff Data Scientist (Bodily Injury Claims)

Clara Analytics

8h•Remote

About The Position

We’re seeking a Staff 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.

Requirements

At least 7 years in Data Science with a strong track record of deploying models into production environments.
Deep experience with Bodily Injury claims, including 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.

Responsibilities

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.