Senior Data Scientist (Healthcare)

TL;DR

Senior Data Scientist (Healthcare): Design, build, validate, and deploy machine learning models and generative AI applications for healthcare organizations with an accent on clinical prediction, population health, operational optimization, and LLM-powered workflows. Focus on feature engineering, MLOps practices, RAG pipelines, and translating complex findings into actionable insights for stakeholders.

Location: United States; must be legally authorized to work in the US without sponsorship. Remote from home office with willingness to travel for onsite meetings as needed.

Company

Healthcare and life sciences technology and consulting firm delivering analytics, optimization, and advisory services to providers, payers, and life sciences organizations.

What you will do

• Design, build, validate, and deploy ML models across the full data science lifecycle including exploratory analysis, feature engineering, and monitoring.
• Develop advanced analytics for clinical prediction, population health, operational optimization, and research enablement.
• Build AI-powered applications using LLM APIs, prompt engineering, and RAG pipelines for clinical and operational workflows.
• Work with diverse healthcare data sources like EHRs, claims, and clinical registries.
• Translate analytical findings into actionable insights for clinical and operational stakeholders.
• Manage documentation, scalable frameworks, and mentor client teams on sustaining deliverables.

Requirements

• 3–5+ years in data science, machine learning, or quantitative role.
• Strong proficiency in Python (pandas, NumPy, scikit-learn) and SQL.
• Hands-on experience with ML models (classification, regression, clustering, time-series).
• MLOps best practices (model versioning, CI/CD, MLflow, monitoring).
• Practical experience with LLM APIs, prompt engineering, and RAG pipelines.
• Experience with cloud platforms (AWS SageMaker/Redshift/S3, Azure ML/Synapse, GCP Vertex AI/BigQuery, Databricks, or Snowflake).
• Strong communication skills for non-technical audiences.

Nice to have

• Healthcare knowledge (EHR, claims, HL7/FHIR, clinical terminologies).
• Population health analytics, risk stratification, or social determinants of health.
• Research workflows (cohort identification, clinical trials, outcomes research).
• Vector databases, embeddings, fine-tuning, or LLM evaluation.
• Data visualization tools (Tableau, Power BI, Looker).
• Revenue cycle or operational analytics experience.
• Advanced degree (Master's/PhD) in quantitative field.

Culture & Benefits

• People-first, values-driven organization emphasizing strong teams and trusted partnerships.
• Competitive salary and hybrid compensation plans.
• Health care (medical, HSA, dental, vision), 401k retirement, life insurance, disability coverage.
• Paid time off (vacation, sick, holidays), training & development fund.
• Work from home with occasional travel.
• Charitable giving opportunities.