Gilead Sciences · 14 hours ago
Director, Data Science - Measurement & Optimization
United States - New Jersey - Parsippany
Full-time
Hybrid
Director/Executive
$206K/yr - $266K/yr
8+ years expGilead Sciences is dedicated to creating a healthier world for all people, focusing on tackling major diseases and improving lives through innovative therapies. As a Director of Data Science - Measurement & Optimization, you will lead the development of data science techniques to drive strategic business decisions and optimize resource allocation within commercial markets. This role involves collaborating with various teams to turn business insights into actionable data solutions and foster a culture of measurement and impact.
BiopharmaBiotechnologyHealth CareManufacturingPharmaceutical
Responsibilities
Lead the development and delivery of models and methodologies to inform and evaluate brands' marketing and sales tactics (e.g., marketing mix, resource allocation) using the latest data science techniques (ANCOVA, Bayesian Statistics, Econometrics, Neural Networks/Logistic, etc.)
Oversee and guide the development and execution of experiments (e.g., A|B and multi-variate tests) to assess the effectiveness of tactics, modifying initiatives as required
Lead the design of KPIs to track the effectiveness of recommendations that have been implemented and the measurement of campaign impact (e.g., ROI, engagement, lift, etc.)
Understand Gilead's commercial business objectives, develop and deploy scalable data science products and insights to influence decisions in marketing, sales, medical, etc
Lead Data science projects end to end including converting unstructured business questions into data science solutions, give guidance to offshore, be a hands-on leader who knows how to code and debug, and communicate with stakeholders
Foster a culture of measurement and impact and incorporate feedback to continuously improve data science models
Bring thought leadership and thorough understanding of statistics, primarily predictive algorithms & methodologies, to construct robust propensity models for impactful commercial use
Create data science products that can be refreshed, reproduced and replicated consistently
Work with other Data Scientists and Analysts to define retraining schedule and measure propensity models for impact
Partner with global teams to cross-pollinate ideas and replicate successful models from other countries and vice versa
Excellent communication and ability to abstract backend complexity when unnecessary
Qualification
Required
Bachelor's Degree and Twelve Years' Experience
OR
Masters' 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 (RF, XGB, LightGBM), SMOTE, etc
Experience in building, implementing and using AI-based solutions with proven business impact
Strong leadership capable of managing initiatives from beginning to end independently
Effective written and verbal communication skills
Degree or above with significant relevant data science/analytics experience
Benchmarking experience in digital and / or emerging AI fields such as generative AI
Preferred
Experience in measuring, implementing, optimizing and using AI-based solutions to establish proven business impact
Experience in designing test control experiments
Experience working with standard pharma and consumer data types and sources such as patient claims, Xponent, Plantrak, sales, activity
Expertise in commonly used pharma datasets such as IQVIA, Symphony, Komodo claims, Optum, Definitive health, Health Verity, EMR/EHR
Expertise in Python including commonly used data science libraries such as numpy, pandas, scikit-learn, seaborn, networkx, etc
Expertise in data science techniques such as ANCOVA, Bayesian Statistics, Econometric modelling, Neural Networks/Logistic, etc
Understanding of cloud-based technologies and tools such as Databricks, AWS, etc
Experience designing measurement solutions in any visualization software (Tableau preferred)
Experience with ex-US (European) markets is not required but highly preferred
Demonstrated product mindset
Familiarity with product management principles
Effective written and verbal communication skills
Strong team player. Inclusive, objective, cross-functional, team member with a positive and solution-oriented mindset
Understanding of emerging data science capabilities (fields, methodologies, algorithms, etc.) and potential application in pharma/health care
Thorough understanding of datasets including their strengths and limitations such as capture rate, projections and acceptable error ranges for different therapeutic spaces
Benefits
Discretionary annual bonus
Discretionary stock-based long-term incentives
Paid time off
Company-sponsored medical, dental, vision, and life insurance plans
Company
Gilead Sciences
Gilead Sciences is a biopharmaceutical company that discovers, develops, manufactures and commercializes therapies for critical diseases.
10001+ employees
H1B Sponsorship
Gilead Sciences has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (269)
2024 (241)
2023 (222)
2022 (208)
2021 (235)
2020 (187)
Funding
Current Stage
Public CompanyTotal Funding
$4.41BKey Investors
Abingworth
2024-11-13Post Ipo Debt· $3.5M
2024-02-29Post Ipo Equity· $210M
2023-09-07Post Ipo Debt· $2B
Leadership Team
Keeley Wettan
Senior Vice President, Legal
Patrick Loerch
Senior Vice President, Clinical Data Science
Recent News
2026-01-23
GlobeNewswire
2026-01-22
Company data provided by crunchbase