Clinical Data Scientist
Phare Health
About Us
Our mission is to make healthcare reimbursement transparent and fair (/phare), so providers can spend more time caring for patients and less time haggling over costs. We specifically focus on the most complex AI challenges that require novel R&D, with a team that blends AI researchers and engineers with clinicians, and payment experts. Backed by General Catalyst, we’re scaling quickly - join us!
The Role
You will join a tight-knit AI team as a hands-on data scientist and resident expert in clinical text, shipping ML systems into production and pushing forward state of the art. Expect to:
Prototype end-to-end text pipelines - clean and normalise raw EHR notes, choose an architecture, train, and evaluate - at the pace of days not months.
Train transformer models - fine-tune large language models for coding, summarisation, and clinical reasoning, then keep them fresh with continuous-learning loops.
Implement LLM workflows - build retrieval-augmented generation (RAG) and lightweight multi-agent chains that output clear, reference-backed answers.
Explore new datasets - run exploratory data analysis, map content to ICD-10, CPT and flag data gaps before modelling.
Productionise your work - convert research prototypes into reliable services with CI/CD, monitoring, and rollback.
Who we're looking for
3+ years applying NLP or data-science to clinical (or similarly complex) text.
Proven ability to take a project from EDA → model design → evaluation → production code in Python (SQL, Pandas, modern ML/NLP libraries).
Hands-on experience training transformer models and building RAG or agent-based LLM pipelines.
Familiar with EHR formats and healthcare ontologies (ICD-10, CPT, LOINC, SNOMED).
Track record operating production-grade ML systems with monitoring and uptime targets.
Bonus points
Peer-reviewed publications or open-source contributions in clinical NLP.
Experience with reinforcement-learning methods such as GRPO (or similar policy-optimisation techniques) for model refinement.
Experience in customer-facing roles communicating data science requirements and gathering specs from end users.
Benefits
Top-of-market compensation (salary + equity)
Flexible PTO & hybrid culture (SoHo HQ 3 days/wk; exceptional remote considered)
Mission-driven, collaborative team
Twice-yearly offsites to align, build, and celebrate.
Hiring Process
Initial application.
Intro call: Discuss your background, career goals, and our mission.
2 x Technical interviews: A programming or system design exercise focused on real-world data challenges.
Referees: We ask for 2 referees who can speak to your professional/technical work
Culture interview: Ways of working, and a chance to ask questions
Offer