Associate Director, Data Science – Commercial

Gilead Sciences

. Bring innovative data science techniques and insights to business to drive and support strategic business decisions .

Posted 10/13/2026full-timeUnited StatesSenior💰 $195,670 - $253,220 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in machine learning algorithms, predictive modeling, and data science product development, with a strong focus on pharma datasets and AI-based solutions. Proven leadership in managing data science initiatives and fostering team collaboration to drive impactful business decisions.

Highest-signal resume keywords

Machine Learning AlgorithmsPredictive ModelingPython and Data Science LibrariesPharma Datasets ExpertiseLeadership in Data Science Initiatives

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning AlgorithmsPredictive ModelingData Science Product DevelopmentStatistical AnalysisAI-Based SolutionsData AnalysisEconometric ModelingNeural NetworksRegression TechniquesClustering Techniques

Soft Skills

Effective CommunicationTeam LeadershipInclusive MindsetCross-Functional CollaborationSolution-Oriented Approach

Tools & Technologies

PythonDatabricksS3NumPyPandasScikit-learnSeabornNetworkxIQVIASymphony

Industry Keywords

Pharma DataPatient ClaimsPredictive SciencesCommercial MarketPatient JourneyData Science InitiativesHealthcare AnalyticsData Science SolutionsBusiness ImpactQuantitative Field

Tech Stack

Tools & technologies

CloudNumpyPandasPythonScikit-Learn

About the role

Key responsibilities & impact

Bring innovative data science techniques and insights to business to drive and support strategic business decisions
Stand up integrated HCP, patient journey, and predictive sciences capabilities at scale for the commercial market
Work closely with integrated insights, commercial operations, patient engagement, and omnichannel analytics leads
Drive industrialization of predictive sciences to understand patient journeys and market triggers
Develop and deploy scalable data science products and insights for marketing, sales, medical, and other business decisions
Lead data science projects end to end, translating unstructured business questions into data science solutions
Provide guidance to offshore teams and serve as a hands-on leader who codes and debugs
Communicate with stakeholders and foster a culture of measurement and impact
Construct robust propensity models using predictive algorithms and methodologies
Create refreshable, reproducible, and replicable data science products
Define retraining schedules and measure propensity-model impact with Data Scientists and Analysts
Partner with global teams to cross-pollinate ideas and replicate successful models
Manage data science initiatives and deliveries for a priority therapeutic area
Build, develop, and motivate a team through hiring, coaching, and mentoring
Create inclusion, develop talent, and empower teams

Requirements

What you’ll need

Bachelor's Degree and Eight Years' Experience OR Master's 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, SMOTE
Experience building, implementing, and using AI-based solutions with proven business impact
Experience working with pharma and consumer data types and sources such as patient claims, Xponent, Plantrak, sales, and activity data
Strong leadership and ability to manage initiatives from beginning to end
Effective written and verbal communication skills
Expertise in pharma datasets such as IQVIA, Symphony, Komodo claims, Optum, Definitive Health, Health Verity, and EMR/EHR
Expertise in Python and data science libraries including NumPy, pandas, scikit-learn, seaborn, and networkx
Expertise in ANCOVA, Bayesian statistics, econometric modeling, neural networks, and logistic methods
Understanding of cloud-based technologies and tools such as Databricks and S3
Demonstrated product mindset and familiarity with product management principles
Strong team player with an inclusive, objective, cross-functional, positive, and solution-oriented mindset
Understanding of emerging data science capabilities and their application in pharma/health care
Thorough understanding of datasets, including capture rates, projections, and acceptable error ranges
Master's degree in a quantitative field with at least 8 years of relevant data science/analytics experience OR undergraduate degree in a quantitative field with at least 10 years of relevant data science/analytics experience

Benefits

Comp & perks

Discretionary annual bonus
Discretionary stock-based long-term incentives
Paid time off
Company-sponsored medical insurance
Company-sponsored dental insurance
Company-sponsored vision insurance
Company-sponsored life insurance