Director, Marketing Sciences

Role Summary

Director, Marketing Sciences at Gilead to lead high-impact, cross-functional initiatives across therapeutic areas that drive strategic value and innovation. Partner with diverse stakeholders and data science peers to establish best practices, streamline operations, and deliver measurable improvements in driving business performance, team efficiency, and cost optimization. Reports to the Sr. Director, Marketing Sciences.

Responsibilities

• Be a partner in driving the industrialization of predictive sciences to help understand the patient journey and triggers robustly for markets.
• Understand Gilead's commercial objectives, develop and deploy scalable data science products and insights to influence decisions in marketing, sales, medical, and related areas.
• Lead data science projects end to end, convert unstructured business questions into data science solutions, provide guidance to offshore teams, and be a hands-on leader who can code and debug.
• Foster a culture of measurement and impact and incorporate feedback to continuously improve data science models.
• Bring thought leadership and thorough understanding of statistics to construct robust propensity models for commercial use.
• Create data science products that can be refreshed, reproduced, and replicated.
• Work with other data scientists to define retraining schedules and measure propensity models for impact.
• Partner with global teams to cross-pollinate ideas and replicate successful models across regions.
• Excellent communication and ability to abstract backend complexity when unnecessary.

Qualifications

• Bachelor's Degree and twelve years' experience or Master's Degree and ten years' experience or PhD and eight years' experience
• Strong working knowledge of machine learning algorithms including regression, clustering, neural networks, Bayesian models, RNN, CNN, tree-based algorithms, SMOTE, etc.
• Experience in building, implementing, and using AI-based solutions with proven business impact
• Strong leadership capable of managing initiatives from start to finish
• Effective written and verbal communication skills

Preferred Experience

• Experience implementing and optimizing AI-based solutions to establish proven business impact
• Experience with pharma/consumer data types and sources (claims, Xponent, Plantrak, sales, activity) and pharma datasets (IQVIA, Symphony, Komodo, Optum, Definitive Health, Health Verity, EMR/HER)
• Expertise in Python and data science libraries (numpy, pandas, scikit-learn, seaborn, networkx, etc.)
• Experience with advanced data science techniques (ANCOVA, Bayesian statistics, econometric modeling, neural networks, etc.)
• Understanding of cloud technologies (e.g., Databricks, S3)
• Experience designing measurement solutions in visualization tools (Tableau preferred)
• Product mindset and familiarity with product management principles
• Strong collaboration skills; inclusive, cross-functional team player
• Understanding of emerging data science capabilities and potential pharma/healthcare applications
• Thorough understanding of datasets, their strengths and limitations, and acceptable error ranges for therapeutic spaces
• Master's degree in a quantitative field with at least 6 years of relevant experience or Bachelor's degree with at least 8 years

Education

• Master's or PhD preferred in a quantitative field; alternative: extensive relevant experience as specified above

Additional Requirements

• Travel requirements are not specified here.