Senior Data Scientist – Pharma

This is a fully remote position, open to applicants in California.

📋 Description

• Create and implement NBA/NBC models by selecting the appropriate action, channel, content, and timing for each customer or healthcare professional (HCP).

• Develop machine learning, deep learning, and reinforcement learning solutions, including contextual bandits, sequential decision models, and policy-based methodologies.

• Construct propensity, response, and uplift models that feed into the decision-making layer.

• Conduct offline policy evaluations and online experiments to assess incremental impacts.

• Manage Databricks training pipelines, encompassing PySpark feature engineering, MLflow tracking, Unity Catalog lineage, and automated evaluation gates.

• Design feedback mechanisms to ensure outcomes are incorporated back into retraining processes.

• Utilize GenAI/LLMs for tasks such as content tagging, insight summarization, and content personalization.

• Collaborate with engineering, marketing technology, and business stakeholders.

• Communicate results effectively to non-technical audiences.

• Provide mentorship to junior data scientists and establish modeling standards.

⛳️ Requirements

• 6 to 8 years of experience in data science or applied machine learning, with practical involvement in NBA, NBC, recommendation systems, or personalization in a production environment.

• Extensive experience with Databricks (including Spark/PySpark, Delta Lake, MLflow; familiarity with Feature Store or Unity Catalog is advantageous).

• Strong foundation in machine learning and deep learning (using PyTorch or TensorFlow) as well as reinforcement learning (such as bandits, Q-learning/DQN, PPO).

• Proficient in Python and SQL.

• Experience transitioning models from prototype to production utilizing MLOps practices (CI/CD, monitoring, and retraining).

• Background in experimentation, A/B testing, and evaluating incrementality.

• Bachelor's or Master's degree in a quantitative field (Master's or PhD is preferred).

• Experience in life sciences or pharmaceutical commercial analytics is preferred but not required.

• Familiarity with CRM, CDP, or marketing automation platforms is preferred but not required.

• Knowledge of causal inference and uplift modeling is preferred but not required.

• Experience with regulated or compliance-sensitive data such as HIPAA is preferred but not required.

• Databricks certifications are preferred but not required.

🏝️ Benefits

• Medical, Dental, Vision coverage.

• Retirement Accounts.

• Long and Short-Term Disability benefits.

• Life Insurance.

• HSA/FSA Accounts (available in the USA).

• Discretionary time-off.

• Opportunities for significant career development.

• Continuous learning and AI upskilling.

• Hands-on exposure to emerging technologies.

• Opportunities to develop expertise in Generative AI, agentic AI, and next-generation data platforms.

• Commitment to equal employment opportunities.