Assoc. Dir, Data Science

Job Description

Mission

• Leverage data science and AI to improve the efficiency and quality of commercial operations. Build a closed loop from target setting resource allocation execution monitoring to review and optimization continuously enhancing coverage quality call effectiveness channel sell-through health and compliance to deliver attributable impact for brand and therapeutic area growth.

Key Responsibilities

• Commercial excellence strategy and operating rhythm: Partner with Sales Marketing Compliance and Finance to identify key levers to improve commercial efficiency; define the annual roadmap and OKRs and embed them into the QBR cadence; establish a unified metric and methodology handbook (KPI/KRI dictionary attribution definitions data lineage).

• Targeting and coverage quota and territory optimization: Develop HCP/HCO segmentation and potential scoring white-space identification and target lists; provide recommendations on coverage and call frequency; design fair quota and territory schemes optimize territory boundaries and call routes; build performance insights and action plans.

• Channel and sell-through health: Build sell-through forecasting and inventory health monitoring (stock-out/slow-moving alerts replenishment recommendations); evaluate distributor performance and optimize channel structure; conduct price and discount consistency and compliance analyses and jointly establish early warning and governance with Finance/Legal.

• Data productization and engineering governance: Build commercial feature and labeling assets (HCP/HCO profiles access/payment environment channel/territory tags behavioral and stickiness features) to drive reuse and versioning; establish end-to-end delivery and governance (model registry CI/CD online/batch scoring monitoring and drift alerts rollback audit trail and documentation); develop frontline self-service analytics and action-oriented dashboards integrated with CRM/business systems and BI platforms.

• Organizational influence and change management: Support managerial decisions with explainable results and create a insightactionreview loop; recruit and develop cross-disciplinary talent; establish technical reviews and post-mortems and codify cases and methodologies; raise frontline data literacy and usage stickiness.

• Compliance and data ethics: Adhere to promotional compliance and privacy regulations (GDPR/CCPA/local requirements); implement data classification minimal-use principles and PII de-identification/anonymization; manage third-party data compliance through vendor assessment contractual controls audit trails and access controls.

Qualifications

• Education and background: Bachelors degree or above in Statistics Computer Science Applied Mathematics Operations Research Economics or related fields (Master/PhD preferred); 710 years of experience in data science/commercial analytics with 3 years of team management or technical leadership; experience in pharma commercial operations/commercial excellence preferred.

• Skills and experience:

• • Business scenarios: Targeting and coverage strategy quota and territory design sell-through and inventory forecasting channel health and price/discount compliance marketing ROI and MMM market access impact assessment.

  • Methods and tools: Machine learning (classification/regression/ranking clustering time series) causal inference and quasi-experiments (matching difference-in-differences synthetic control) optimization (linear/integer programming heuristics).

  • Tech stack: Python (Pandas/NumPy/Scikit-learn/Statsmodels) SQL BI (Power BI/Tableau/Looker) big data and orchestration (Spark Airflow/Dagster) LLMs etc.

  • Governance and explainability: SHAP/LIME feature/model drift monitoring bias and fairness assessment audit-ready documentation.

• Soft skills: Strong commercial acumen and operational understanding; outstanding cross-functional communication influence and change management; proven team building and coaching ability to foster a learning-oriented and delivery-focused culture.

Required Skills:

Preferred Skills:

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