Senior Data Scientist
Prominence Advisors
full-time
Posted on:
Location Type: Remote
Location: United States
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Job Level
Tech Stack
About the role
- Design, build, validate, and deploy machine learning models across the full data science lifecycle, including exploratory analysis, feature engineering, model development, validation, deployment, and monitoring.
- Develop advanced analytics solutions for clinical prediction, population health, operational optimization, and research enablement.
- Build AI-powered applications leveraging LLM APIs, prompt engineering, and RAG pipelines to support clinical and operational workflows.
- Ability to work with diverse healthcare data sources including EHRs, claims, and clinical registries.
- Translate complex analytical findings into meaningful, actionable insights for clinical and operational stakeholders.
- Manage documentation of best practices and scalable frameworks that can be applied across client engagements.
- Mentor and guide client counterparts to build the skills needed to sustain and expand on project deliverables.
Requirements
- 3–5+ years of professional experience in data science, machine learning, or a closely related quantitative role.
- Strong proficiency in Python for data science (pandas, NumPy, scikit-learn) and SQL for data extraction and manipulation.
- Hands-on experience building, validating, and deploying machine learning models (classification, regression, clustering, time-series forecasting).
- Experience with MLOps best practices (model versioning, CI/CD for ML, experiment tracking with MLflow or similar, continuous monitoring).
- Practical experience building AI-powered solutions using LLM APIs, prompt engineering, and RAG pipelines.
- Experience with cloud-based data and ML platforms, including at least one of the following: AWS (SageMaker, Redshift, S3), Azure (Azure ML, Synapse, Data Factory), GCP (Vertex AI, BigQuery), Databricks, or Snowflake.
- Strong communication skills with the ability to present technical findings to non-technical audiences.
- Healthcare industry knowledge and experience including EHR data, claims, HL7/FHIR, clinical terminologies.
- Experience with population health analytics, risk stratification, or social determinants of health.
- Understanding of research enablement workflows including cohort identification, clinical trial matching, and outcomes research.
- Experience with vector databases, embeddings, fine-tuning, or LLM evaluation frameworks.
- Familiarity with data visualization and BI tools (Tableau, Power BI, or Looker).
- Revenue cycle, staffing optimization, or other operational analytics experience.
- Advanced degree (Master's or PhD) in a quantitative field such as computer science, statistics, biostatistics, or a related discipline
Benefits
- Competitive Salaried and Hybrid Compensation Plans
- Health Care Plan (Medical, HSAs, Dental & Vision)
- Retirement Plan (401k)
- Life Insurance (Basic, Voluntary & AD&D)
- Dependent & Health Savings Accounts
- Short Term & Long Term Disability
- Paid Time Off (Vacation/Sick & Public Holidays)
- Training & Development Fund
- Work From Home
- Charitable Giving to Causes You Believe In
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningdata sciencePythonSQLMLOpsAI-powered solutionsfeature engineeringmodel validationmodel deploymentdata extraction
Soft Skills
strong communication skillsmentoringtranslating analytical findingscollaborationguiding stakeholders
Certifications
Master's degreePhD