Principal Data Scientist - Pharma Commercial Analytics
About The Position
Tiger Analytics is seeking a data science leader with pharmaceutical commercial analytics, patient-level modeling, and healthcare data science experience. The role involves using US healthcare claims and real-world data (RWD) to develop predictive models, generate actionable insights, and optimize HCP engagement and commercial strategies. It combines technical expertise and leadership with direct client engagement and presentations to senior stakeholders. The position offers significant career development opportunities in a small, fast-growing, challenging, and entrepreneurial environment, with a high degree of individual responsibility. Tiger Analytics provides equal employment opportunities without regard to protected characteristics or status under applicable federal, state, or local law.
Requirements
- Strong experience in pharmaceutical commercial analytics and healthcare data science.
- Hands-on experience with US healthcare claims and real-world data, using platforms or providers 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 for 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 (RWD), 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.
Benefits
- Significant career development opportunities as the company grows.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
Education Level
No Education Listed
