One of the world’s leading pharmaceutical manufacturers, dedicated to delivering life-changing medicines and therapies across global markets. As they advance their digital and data transformation, they are investing in cutting-edge analytics to drive smarter, more personalized customer engagement.

The Role

Our client is looking for a skilled and strategically minded Omnichannel Lead in an individual contributor role to join either their Oncology or Women’s Health department which will help grow out the commercial analytics function,

This is a hands-on modeling role with strong cross-functional exposure, where you will play a pivotal role in building & developing Marketing Mix Modeling (MMM).

Develop and maintain robust Marketing Mix Models (MMM) in Python to inform investment decisions across oncology and women’s health portfolios.
Build scalable Next Best Action / Next Best Engagement models to support HCP engagement strategies and optimize omnichannel performance.
Partner with media agencies, brand teams, and digital marketers to integrate and utilize complex digital media data in modeling efforts.
Leverage personalization techniques and recommender models to tailor messaging, timing, and channels to individual HCP preferences and behaviors.
Translate complex modeling outputs into actionable commercial strategies through clear and compelling storytelling.
Serve as a thought partner to stakeholders across Commercial, Medical Affairs, and Insights—driving model adoption and continuous refinement.
Stay up to date on therapeutic trends, data sources, and digital innovation in oncology and women’s health.

Your Skills & Experience

Strong Python programming skills with a track record of developing and deploying statistical models in a production setting.
Deep expertise in Marketing Mix Modeling—must have built MMMs independently with proven business impact.
Experience working with digital marketing data, media mix inputs, CRM systems, and 3rd-party healthcare datasets.
Familiarity with personalization models or recommender systems, ideally within a healthcare or life sciences context.
Strong communication and stakeholder management skills—able to influence and collaborate across commercial and technical teams.