Sr Manager, Marketing Sciences

Gilead Sciences, Inc.•Parsippany, NJ

52d

About The Position

Gilead's mission is to discover, develop, and deliver therapies that will improve the lives of patients with life-threatening illnesses worldwide. We are seeking a visionary Sr. Manager, Data Science, to drive high-impact, cross-functional initiatives across therapeutic areas (TAs) that drive strategic value and innovation throughout the organization. This role will 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. The ideal candidate will bring knowledge in healthcare data and a strong track record of applying advanced analytics and AI/ML techniques to inform decision-making and improve patient outcomes. This role will drive initiatives such as: Defining and implementing best practices in data science across teams and TAs; Championing scalable, reusable solutions that accelerate insight generation and operational excellence; Drive cross TAs and cross functional data science initiatives including advancing cross-functional collaborations on initiatives like the Medical Digital Assistant, HCP to account mapping, Stigma measurement and etc. Success in this role requires technical depth, and the ability to influence and align stakeholders across functions to shape the future of data science within the enterprise. Hands on functional expertise, highly collaborative mindset and leadership skillsets required. This role reports directly to the Sr. Director, Marketing Sciences and may be based in Parsippany (NJ), or Foster City (CA).

Requirements

Bachelor's Degree and Eight Years' Experience
OR
Masters' Degree and Six Years' Experience
OR
PhD and Two 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 and etc.
Experience in building, implementing and using AI-based solutions with proven business impact
Strong leadership that be able to manage initiatives from beginning to end himself/herself
Effective written and verbal communication skills

Nice To Haves

Experience in implementing, optimizing and using AI-based solutions to establish proven business impact
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/HER
Expertise in Python including commonly used data science libraries such as numpy, pandas, scikit-learn, seaborn, networkx, etc.
Expertise in data science techniques such ANCOVA, Bayesian Statistics, Econometric modeling, Neural Networks/Logistic, etc.
Understanding of cloud-based technologies and tools such as Databricks, S3, etc.
Experience designing measurement solutions in any visualization software (Tableau 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

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 business objectives, develop and deploy scalable data science products and insights to influence decisions in marketing, sales, medical and etc.
Drive Data science projects end to end include convert unconstructured business questions into data science solutions, be a hands-on expert who knows how to code and debug, communicate with stakeholders and etc.
Foster a culture of measurement and impact and incorporate feedback to continuously improve data science models
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
Work with other Data Scientists 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 where it is not needed

Benefits

This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package. Benefits include company-sponsored medical, dental, vision, and life insurance plans.

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