Associate Director, Business Insights & Analytics Data Scientist

Cytokinetics, Inc.; Radnor (Delaware County); On-site; USD 221,000 - 257,000; Full time

Job summary

Cytokinetics, Inc. in Radnor, PA is seeking a senior data science leader to drive advanced analytics across marketing, sales, and patient services. You will own the commercial data science roadmap, build ML models, and partner with executives to translate insights into strategic decisions.

The role emphasizes real‑world data analysis, measurement studies, and scalable self‑serve insights across BI platforms. Strong communication and executive storytelling are essential for success.

Qualifications

• Advanced analytics, ML, and predictive modeling experience.
• Experience building dashboards and insights for executives.
• Strong communication and stakeholder management.

Responsibilities

• Partner with internal stakeholders to frame key business questions as tractable analytical problems.
• Analyze business and market data to identify trends and optimization opportunities across brands.
• Design, build, and deploy supervised and unsupervised ML models and measurement studies.
• Develop patient and customer analytics insights and predictive models to guide marketing and field actions.

Skills

Python

SQL

Machine Learning

Statistics

Experimentation

Data storytelling

Cross-functional collaboration

Dashboards

Education

Master’s or PhD in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field

Bachelor’s degree with 10+ years of experience

Tools

Tableau

Power BI

Jupyter

Job description

Cytokinetics is a specialty cardiovascular biopharmaceutical company, building on its over 25 years of pioneering scientific innovations in muscle biology, and advancing a pipeline of potential new medicines for patients suffering from diseases of cardiac muscle dysfunction.

As a key member of the Business Insights and Analytics team within the commercial domain of Cytokinetics, you will apply advanced analytics, machine learning, and AI to a broad array of data sources (claims, payer, sales, SP, ex-factory, channel, digital engagement, field, patient services, etc.) to drive business decision making across marketing, sales, patient operations, and market access. Owning the commercial data science methodology and roadmap, you will partner directly with Marketing, Value and Access, Sales, Operations, IT, and Finance leaders, with a clear line of sight from your models to business and patient impact. Your work will include building and deploying ML models and other AI capabilities across commercial use cases, designing measurement studies and experiments to optimize spend, driving in‑line and pre‑launch market and performance insights, delivering scalable, automated insights and analytics across BI and other platforms, and collaborating with internal stakeholders to shape commercial and advanced analytics strategy. As Cytokinetics commercial is in a phase of rapid growth, you will also be essential to support strategic decision making by uncovering business performance and insights that require deep and complex exploration of large data sets. This role blends technical depth, business acumen, and the ability to communicate insights effectively to executive and other non‑technical audiences. The ideal candidate has a strong background in building scalable advanced analytics and predictive models, analyzing market trends and the competitive landscape, and partnering closely across the insights, data, and IT teams to uncover opportunities that create further value for patients.

Our employees come from different backgrounds, and we celebrate those differences.

Cytokinetics is an Equal Opportunity Employer.

Our passion is anchored in robust scientific thinking, grounded in integrity and critical thinking. We keep the patient front and center in all we do – all actions and decisions are in service of the patient and their caregivers. We champion integrity, ethics, doing the right thing, and being our best selves.

Responsibilities

• Business Partnership & Problem Framing – Act as a strategic partner to internal stakeholders by framing key business questions as tractable analytical problems that align to brand objectives. Partner cross‑functionally to understand commercial strategies, prioritize use cases by expected business impact, and translate business needs into data science and AI solutions.
• Business, Market & Performance Insights – Analyze business performance and market data from industry (e.g., anonymized longitudinal patient claims data, remittance claims, payer policy and lives data) and internal (e.g., field and digital customer interactions, sales data) sources to answer key business questions, identify trends, and proactively uncover optimization opportunities across in‑line and pre‑launch brands.
• Machine Learning, Measurement & Advanced Analytics – Design, build, and deploy supervised and unsupervised ML models, including classification, regression, time‑series, clustering, and causal/uplift modeling, taking solutions from feature engineering through validation, production deployment, and monitoring. Design and analyze measurement studies and experiments (e.g., A/B and holdout tests, incrementality) and apply ML and other predictive capabilities to marketing mix models to improve investment decisions and optimize spend across channels.
• Patient & Customer Analytics – Conduct patient analytics using real‑world data (RWD) sources such as anonymized longitudinal patient claims and lab/diagnostic testing data to characterize patient populations, treatment patterns, and unmet needs. Analyze patient journeys (e.g., diagnosis, referral, treatment initiation, and persistence) to identify trends and to predict and size performance opportunities and gaps. Develop recommender systems to target commercial action based on patient and HCP data. Develop predictive models to anticipate customer needs, improve customer experience, and optimize promotional efforts across field and digital channels (e.g., segmentation, targeting, and next‑best‑action).
• Insight Delivery & Automation – Partner with BI and IT teams to design intuitive dashboards and self‑service tools, standardize metrics, consolidate redundant reports, and automate recurring reporting and analytics so insights reach stakeholders at scale. Partner with internal data strategy and data governance to ensure consistency and standardization in metric definition and use through approved data foundations. Ensure metric understanding with key stakeholders and be a steward for best practices in standardization and governance.
• Communication & Influence – Translate analytical results into compelling narratives and recommendations that earn stakeholder buy‑in and drive action on data‑driven initiatives. Communicate complex technical concepts tailored to a wide variety of partners including marketing, sales, market access, finance, and legal/compliance.

Essential Skills and Experience

• 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, with 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 to translate analytical outputs into actionable dashboards for executive and business audiences.
• Broad domain knowledge of pharmaceutical commercial functions (e.g., marketing, sales, market access, patient services) and the data and technology environments that support them.
• 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.

Preferred Skills and Experience

• Experience with Machine Learning Operations (MLOps) tools and practices (e.g., CI/CD, experiment tracking, and model monitoring) to maintain model stability and scalability.
• Experience with Generative AI/LLM and agentic models.

Pay Range

The expected salary range for this position based on the primary location of Radnor, PA is $220,500 - $257,250. The base pay offered will take into account internal equity and may vary depending on the candidate’s geographic region, job‑related knowledge, skills, and experience among other factors. Base salary is just one component of our competitive total compensation package, which includes equity in the form of stock options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401(k) retirement benefits with employer match, learning and wellness stipends, and paid time off. Benefit details may vary by jurisdiction.