Lead Data Scientist, Pharma Commercial Analytics

Tiger Analytics Inc.; Princeton (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

Tiger Analytics Inc. in Princeton, NJ is seeking a Lead Data Scientist to drive pharmaceutical commercial analytics and healthcare data science initiatives.

You will develop patient- and HCP-level models, lead a client-facing data science team, and translate business challenges into scalable analytics solutions. Responsibilities include building predictive and multichannel engagement models, conducting experiments with lift measurements, and applying explainable AI techniques (SHAP, gradient

Qualifications

• Extensive experience in pharmaceutical commercial analytics and healthcare data science.
• Hands-on experience with US healthcare claims and real-world data (RWD).
• Strong Python and SQL proficiency for data processing and modeling.
• Experience leading client-facing data science teams and communicating results to senior stakeholders.

Responsibilities

• Develop patient- and HCP-level models to support patient identification and therapy persistence.
• Build predictive models and multichannel engagement analytics to optimize campaigns and engagement.
• Design experiments with holdout groups and lift measurement to assess campaign effectiveness.
• Apply explainable machine learning techniques (e.g., SHAP, gradient boosting) to improve model transparency.
• Analyze US claims, RWD, CRM, and promotional data to generate actionable insights.
• Lead a client-facing data science team, ensuring high-quality delivery and alignment with client objectives.
• Present analytical findings and strategic recommendations to brand leadership.

Skills

Pharma analytics

Healthcare data science

Predictive modeling

Python

SQL

Tools

Databricks

Snowflake

SHAP

Job description

Tiger Analytics Inc. in Princeton, NJ is seeking a Lead Data Scientist to drive pharmaceutical commercial analytics and healthcare data science initiatives.

You will develop patient- and HCP-level models, lead a client-facing data science team, and translate business challenges into scalable analytics solutions. Responsibilities include building predictive and multichannel engagement models, conducting experiments with lift measurements, and applying explainable AI techniques (SHAP, gradient