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-$110/hour (W2)
• Work Arrangement: Remote (U.S.); working hours aligned to Pacific Time
• Duration: 12-month contract (long-term; extension possible)

• 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

• 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

• 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

• 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