Associate Director, Commercial Data Science

Cytokinetics

. Apply advanced analytics, machine learning, and AI to claims, payer, sales, specialty pharmacy, ex-factory, channel, digital engagement, field, and patient services data .

Posted 11/6/2026full-timeUnited StatesSenior💰 $220,500 - $257,250 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in advanced analytics, machine learning, and AI applications within commercial contexts, with a strong focus on statistical modeling, data-driven decision-making, and cross-functional collaboration. Proficient in translating complex analytical results into actionable insights for stakeholders across various business functions.

Highest-signal resume keywords

Machine LearningStatistical ModelingPython ProgrammingData Science MethodologyMarketing Mix Modeling

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningStatistical AnalysisPredictive ModelingCausal InferenceA/B TestingData AnalyticsCloud-Based Notebook EnvironmentsGenerative AIML OperationsData Visualization

Soft Skills

CommunicationInterpersonal SkillsInfluencing StakeholdersCross-Functional CollaborationData-Driven Storytelling

Tools & Technologies

PythonSQLTableauPower BIJupyter

Industry Keywords

Pharmaceutical Commercial FunctionsDigital EngagementPatient AnalyticsMarket AccessHealth Care Datasets

Tech Stack

Tools & technologies

CloudPythonSQLTableau

About the role

Key responsibilities & impact

Apply advanced analytics, machine learning, and AI to claims, payer, sales, specialty pharmacy, ex-factory, channel, digital engagement, field, and patient services data
Own the commercial data science methodology and roadmap
Partner with Marketing, Value and Access, Sales, Operations, IT, and Finance leaders
Build and deploy ML models and AI capabilities across commercial use cases
Design measurement studies and experiments to optimize spend
Drive in-line and pre-launch market and performance insights
Deliver scalable, automated insights and analytics across BI and other platforms
Shape commercial and advanced analytics strategy
Frame business questions as analytical problems aligned to brand objectives
Prioritize use cases by expected business impact and translate business needs into data science and AI solutions
Analyze business performance and market data to identify trends and optimization opportunities
Design, build, validate, deploy, and monitor supervised and unsupervised ML models
Design and analyze A/B tests, holdout tests, incrementality studies, and marketing mix models
Conduct patient analytics using real-world data to characterize populations, treatment patterns, and unmet needs
Analyze patient journeys and predict and size performance opportunities and gaps
Develop recommender systems and predictive models for commercial action, customer experience, and promotional optimization
Partner with BI and IT teams to design dashboards and self-service tools, standardize metrics, consolidate reports, and automate recurring reporting
Support data strategy and governance to ensure metric consistency and standardization
Translate analytical results into narratives and recommendations that drive action
Communicate technical concepts to marketing, sales, market access, finance, and legal/compliance stakeholders

Requirements

What you’ll need

Master’s or PhD in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field with 7+ years of hands-on experience in Data Science, Machine Learning, Advanced Analytics, and/or related disciplines; alternatively, a Bachelor’s degree in the above fields with 10+ years of similar hands-on experience
Deep expertise in statistical and predictive modeling, machine learning, causal inference, and experimentation and measurement
Expertise in promotional effectiveness, marketing mix modeling (MMM), multi-touch attribution (MTA), digital and web analytics, A/B testing, and media performance analysis
Strong proficiency in Python, SQL, and statistical analysis
Experience working in cloud-based notebook environments (e.g., Jupyter) on large-scale health care datasets
Track record of deploying and monitoring ML models in production to address commercial use cases
Working proficiency with BI tools such as Tableau or Power BI
Broad domain knowledge of pharmaceutical commercial functions and supporting data and technology environments
Excellent communication and interpersonal skills with the ability to influence cross-functional and executive stakeholders through data-driven storytelling
Demonstrated success driving cross-functional initiatives from ideation through production
Experience with Machine Learning Operations (MLOps) tools and practices, such as CI/CD, experiment tracking, and model monitoring
Experience with Generative AI/LLM and agentic models

Benefits

Comp & perks

Equity in the form of stock options and/or restricted stock units
Comprehensive health, dental, vision, life and disability insurance coverage
401k retirement benefits with employer match
Learning stipends
Wellness stipends
Paid time off