Associate Director, Business Insights & Analytics Data Scientist

Cytokinetics; EE. UU.; Presencial; USD 221.000 - 257.000; Jornada completa

Descripción de la vacante

Cytokinetics is seeking a Senior Data Scientist to drive advanced analytics across commercial data sources, applying ML and predictive models to optimize marketing, sales, and patient services strategies.

The role partners with Marketing, Value and Access, Sales, Operations, IT, and Finance to deliver scalable insights and governance for data foundations. Strong communication and production ML experience are essential.

Formación

• Advanced degree with hands-on data science and analytics experience.
• Proven expertise in modeling, experimentation, and measurement.
• Experience with MMM, MTA, A/B testing, and media analysis.

Responsabilidades

• Frame business questions into tractable analytical problems aligned to objectives.
• Analyze data from claims, payer, sales, and digital channels to identify trends.
• Design, build, and deploy ML models from feature engineering to monitoring.
• Conduct patient analytics using real-world data and predict opportunities.
• Develop dashboards and self-service tools with BI teams for scalable insights.
• Translate results into narratives for executive stakeholders.

Conocimientos

Data science

Machine learning

Advanced analytics

Python

SQL

BI visualization

Communication

Cross-functional collaboration

Educación

Master's or PhD in Data Science or related field

Bachelor's degree in Data Science or related field

Herramientas

Python

SQL

Tableau/Power BI

Jupyter

Cloud notebooks

Descripción del empleo

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.

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, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.

Our employees come from different backgrounds, and we celebrate those differences. We are looking for the best candidates for our open roles, but do not expect applicants to meet every qualification in order to be considered.

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.

Cytokinetics is an Equal Opportunity Employer