Director, Data Science (Personalized Customer Engagement)

Quick Facts

• Role: Director of Data Science supporting Personalized Customer Engagement for the US oncology market

• Focus: Data-driven insights, targeting/segmentation models, and self-service analytics/AI decision support for omnichannel engagement

Description

Lead data science efforts to translate business needs into analytical plans and actionable insights that inform launch and go-to-market strategies and commercial objectives. Build targeting and segmentation models for the Oncology business to allocate promotional resources across channels, brands, and customer segments. Develop self-service analytics, AI solutions, and decision-support capabilities (including agentic/automation-enabled approaches) while establishing KPIs and measurement standards across omnichannel engagement.

Responsibilities

• Translate business priorities into analytical plans that answer business questions with actionable insights

• Communicate advanced analytics to stakeholders to support business decisions

• Analyze data from disparate sources (including claims/EMR and other datasets) to generate commercial strategy insights

• Stay current on analytical methodologies (including GenAI) to enhance organizational capabilities

• Contribute to experimentation (idea generation/incubation/testing) with measurable improvement criteria

• Develop clear data narratives (“data story”) and communicate effectively with business stakeholders

• Lead and mentor a team of data scientists and business analysts (onshore/offshore)

• Guide omnichannel targeting and segmentation tactics using predictive and machine learning models; emphasize automation, standardization, and agentic AI enablement across the oncology portfolio

Requirements

• BS (or equivalent) in Data Science, Mathematics, Economics, Computer Science, Statistics, Decision Science, Marketing, Engineering, Public Health, or equivalent scientific/commercial discipline

• 7+ years of relevant experience delivering complex analytical projects in pharmaceutical, biotech, consulting, or healthcare

• Self-motivated, able to work independently

• Storytelling and executive presence with senior leaders

• Strong stakeholder management in matrixed organizations

• Business acumen and consultative skills to translate commercial strategy into detailed analytics standards/questions

• Strong organizational and project management skills

• Innovation with experimentation mindset; curiosity about agentic AI and automation for commercial analytics

• Understanding of responsible AI use in regulated environments (data privacy, validation)

• Ability to develop efficient programming code and software assets for advanced analytics

• Proven data science experience with advanced statistics and ML/AI

• Knowledge of ML and descriptive algorithms/modeling using Python, R, SAS, and SQL

Benefits

• Annual bonus and long-term incentive, if applicable

• Comprehensive benefits package: medical, dental, vision, retirement (401(k)), paid holidays, vacation, and compassionate/sick days