Principal Data Scientist - Pharma Commercial Analytics

Tiger Analytics Inc.•Lawrenceville, PA

About The Position

Tiger Analytics is seeking a Principal Data Scientist with strong experience in pharmaceutical commercial analytics, patient-level modeling, and healthcare data science. The role involves using US healthcare claims and real-world data (RWD) to build predictive models, generate actionable insights, and optimize healthcare professional (HCP) engagement and commercial strategies. The position calls for technical expertise, leadership, direct client engagement, and the ability to present analytical findings to senior stakeholders. The Principal Data Scientist will develop patient- and HCP-level models, build analytics solutions for next-best-action recommendations and multichannel engagement, and assess commercial campaign effectiveness through experimental design and lift measurement. The role also includes analyzing claims, RWD, CRM, and promotional data; working with large datasets and modern data platforms; leading a client-facing data science team; and collaborating across functions to deliver scalable solutions aligned with business objectives. The company describes itself as a fast-growing AI services firm working with major organizations on AI, Generative AI, data science, data engineering, and advanced analytics. It highlights significant career development opportunities and an entrepreneurial environment with substantial individual responsibility. Tiger Analytics provides equal employment opportunities without regard to protected characteristics under applicable law.

Requirements

Strong experience in pharmaceutical commercial analytics and healthcare data science.
Hands-on experience with US healthcare claims and real-world data, using providers or platforms such as IQVIA, Komodo Health, or PurpleLab.
Experience with Veeva CRM data and pharmaceutical promotional data.
Expertise in patient-level and HCP-level modeling, including patient identification, treatment switching, and persistence.
Experience developing next-best-action models and multichannel analytics solutions.
Strong knowledge of experimental design, holdout strategies, and campaign lift measurement.
Proficiency in Python and SQL, with experience using Databricks or Snowflake.
Experience with gradient boosting techniques and explainable AI methods such as SHAP.
Proven ability to lead data science teams, manage client relationships, and communicate insights to senior stakeholders.

Responsibilities

Develop patient- and HCP-level models to support patient identification, treatment switching, and therapy persistence.
Build predictive models and analytics solutions for next-best-action recommendations and multichannel engagement strategies.
Design and evaluate experiments, including holdout groups and lift measurement, to assess commercial campaign effectiveness.
Apply explainable machine learning techniques, including gradient boosting and SHAP, to improve model transparency and interpretability.
Analyze US healthcare claims, real-world data, CRM, and promotional data to generate actionable business insights.
Work with large datasets using Python, SQL, and platforms such as Databricks or Snowflake.
Lead a client-facing data science team, ensuring high-quality delivery and alignment with business objectives.
Present analytical findings, model outcomes, and strategic recommendations to brand leadership and other senior stakeholders.
Collaborate with cross-functional teams to translate business challenges into scalable data science solutions.