This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
We are seeking a Senior Clinical Data Scientist to join the Catalysts team, focused on applied intelligence solutions for Truveta. This role focuses on building the concrete intelligence assets that intelligence uses to solve defined healthcare problems correctly and safely. You will work on concrete problem types such as safety monitoring, cohort feasibility, HEOR analyses, clinical trial workflows, and operational oversight, and be responsible for directly creating the knowledge assets, examples, and guardrails that intelligence uses to support these problems effectively and safely. A core part of the role is creating and maintaining practical intelligence assets that intelligence directly uses to support specific, repeatable solutions. These assets are contributed into a shared knowledge base maintained by the broader Catalysts team. You will also influence how intelligence consumes and applies knowledge by producing clear, reusable assets that translate complex technical and domain concepts into forms usable by both intelligence systems and non technical stakeholders.
Job Responsibility:
Independently build small scale, concrete intelligence solutions for specific healthcare problems by creating the required knowledge assets, examples, reference analyses, and guardrails that allow intelligence to answer the right questions and respect clear boundaries, within current platform capabilities
Break down healthcare problems in areas such as clinical research, HEOR, and clinical trials into the concrete assumptions, decision points, and data considerations that intelligence needs to handle correctly
Create and maintain the domain knowledge, guidelines, templates, and decision logic that intelligence systems need in order to perform effectively in each problem domain
Shape how intelligence agents operate at a practical level by defining task breakdowns, decision logic, and required knowledge, working within current platform constraints
Work with domain experts and users to extract assumptions, heuristics, and expertise, and convert them into structured inputs that intelligence systems can reliably consume
Apply an understanding of how generative AI systems retrieve and reason over knowledge to improve correctness, safety, and consistency of intelligence outputs, using concrete examples and test questions
Define and validate constraints, exclusions, and limitations to ensure intelligence outputs are appropriate, trustworthy, and aligned with real world healthcare use
Work closely with colleagues across the Catalysts team, contributing domain expertise, intelligence design, and reusable assets into a shared knowledge base, and collaborating as peers on intelligence solutions rather than owning a separate execution pipeline
Requirements:
Bachelor’s degree or equivalent experience in a quantitative or technical field such as computer science, data science, statistics, engineering, or a related discipline
Strong understanding of how large language models consume, retrieve, and reason over knowledge, and how to structure information so it can be used efficiently and reliably by intelligence systems
Solid understanding of healthcare problem spaces such as clinical research, HEOR, clinical trials, and healthcare operations, and the types of questions and decisions users need support with
Hands on experience using generative AI tools to synthesize, generate, and refine knowledge assets including guidance, templates, prompts, and structured explanations
Ability to design and prototype applied intelligence solutions for specific problem types by combining domain knowledge, templates, prompts, guardrails, and workflows
Comfortable writing and reviewing production quality analysis code (e.g., SQL, Python, or R) to prototype analyses, validate logic, and create reusable examples that intelligence and teammates can reuse
Create clear, reusable intelligence assets by synthesizing expert input or authoring directly, translate technical and domain specific concepts into guidance that is understandable and actionable for a wide range of audiences, and explicitly define exclusions and limitations where intelligence should not provide answers
Nice to have:
Experience working with healthcare or EHR data, including awareness of common data quality issues, biases, and clinical context
Experience designing, evaluating, or contributing to decision support systems, recommendations, or intelligent assistants
Background in product analytics, applied research, or applied machine learning in support of real world decision making
Experience building more complex analytical workflows, reusable code libraries, or data products that others rely on, even if this is not the primary focus of the role
Experience translating expert knowledge into structured guidance, documentation, schemas, or training materials
Teaching, mentoring, or enablement experience with analysts, researchers, or cross functional teams
What we offer:
Interesting and meaningful work for every career stage
Comprehensive benefits with strong medical, dental and vision insurance plans
401K plan
Professional development & training opportunities for continuous learning
Work/life autonomy via flexible work hours and flexible paid time off
Generous parental leave
Regular team activities (virtual and in-person)
Additional compensation such as incentive pay and stock options for certain roles