Data Scientist
- Contract
- Remote (U.S.)
- Pacific Time Hours Join a Biotech organization for a 6-month contract with likely extensions.
This provides the opportunity to work within a high-impact commercial analytics team building predictive modeling, Next Best Action, and GenAI-enabled solutions that improve how healthcare customers are engaged across channels. This is a long-term, fully remote contract for a hands-on data scientist who can deliver production-grade ML and influence stakeholders with clear, actionable insights. The ideal candidate will have 5+ years (MS) or 3+ years (PhD) or 10+ years (BS) in data science/ML, strong Python, R, and SQL experience building end-to-end ML pipelines and MLOps practices, familiarity with modern data platforms (e.g., Databricks and cloud), and strong communication skills; life sciences/commercial analytics and GenAI experience are strong pluses. Opportunity offers an opportunity to work with a well-known organization on a remote basis and within a 6-month contract with likely extensions.
Benefits Pay Range :
$90
Work Arrangement :
Remote (U.S.); working hours aligned to
Pacific Time Duration :
12-month contract (long-term; extension possible) Responsibilities Develop and deploy predictive models to forecast key patient and customer events (e.g., therapy initiation and switching) Build and scale "next best action" models to optimize HCP engagement across channels and products Apply advanced machine learning methods including regression, classification, and natural language processing Design and implement multi-touch attribution approaches for customer journey measurement and optimization Integrate Generative AI capabilities into commercial analytics workflows (planning, personalization, and AI-assisted pipeline interfaces) Own end-to-end ML pipelines: data ingestion, feature engineering, model training, evaluation, and deployment Implement MLOps best practices including model versioning, monitoring, and automated retraining Support scalable deployment through CI/CD and API-first patterns Partner with Sales, Marketing, and Analytics stakeholders to translate business questions into data science solutions Deliver clear, actionable insights and recommendations to senior stakeholders Collaborate closely with data engineering and analytics teams to ensure production-ready solutions and adoption Work with large healthcare/commercial datasets (claims, EHR/EMR, CRM, digital engagement) while maintaining privacy and compliance expectations Required Qualifications Master's or PhD in Data Science, Computer Science, Statistics, Operations Research, Mathematics, or a related quantitative field 5-7+ years of experience (Master's) or 3-5+ years (PhD) in data science, machine learning, or advanced analytics Strong Python (preferred) or R experience Strong SQL skills and comfort working with large datasets Solid understanding of supervised/unsupervised learning, statistical analysis, and experimental design Experience building production-grade ML solutions (not just notebooks) Familiarity with modern data/ML platforms (e.g., Databricks; major cloud environments such as AWS/Azure) Experience with ML deployment patterns (REST APIs) and containerization (Docker) Ability to communicate results clearly to technical and non-technical audiences Preferred Qualifications Life sciences, pharmaceutical, or healthcare commercial analytics experience Experience with HCP targeting/segmentation, omnichannel analytics, or sales/marketing effectiveness modeling Experience with next best action frameworks and/or promotional response modeling Hands-on exposure to GenAI/LLM solutions (prompting, RAG, agentic workflows) and vector/embedding concepts Experience with BI tools such as Power BI and/or Tableau Successful Candidate Deliverables Deliver scalable AI/ML and GenAI solutions that improve commercial decision-making Enable faster, smarter cross-channel engagement strategies through measurable analytics impact Deploy reliable, monitored ML pipelines and automation that are adopted by business teams
