Director, Data Product & Analytics Engineering – Pathway AI

About BioMarin

About Digital, Technology & AI and Patient FIND

Role Summary

Patient FIND Data Translation and Technical Requirements

• Develop, own, and be accountable for the technical requirements framework for Patient FIND.
• Own and maintain an integrated view of Patient FIND use cases, source data, shared data layers, technical dependencies, implementation risks, and delivery priorities.
• Identify gaps in signals, data quality, processes, and technical approaches, and recommend scalable solutions.
• Lead technical translation and alignment across business, scientific, engineering, analytics, AI/ML, governance, and activation teams.

Analytics Engineering and Reusable Data Products

• Develop, own, and deliver governed Patient FIND data products and analytical datasets across claims, EHR/EMR, lab, Rx, CRM, specialty pharmacy, digital engagement, and other approved data sources.
• Establish the reusable data product foundation and standards for feature logic, cohort definitions, metadata, lineage, quality controls, and analytical documentation.
• Ensure Patient FIND use cases build upon reusable assets and enterprise design patterns rather than creating one-off solutions.
• Define and execute a sequenced technical roadmap that prioritizes foundational capabilities, accelerates implementation, and supports long-term scale.

Data Science and Advanced Analytics Enablement

• Define and deliver the analytical data foundation required for patient identification, segmentation, HCP prioritization, predictive modeling, treatment progression, adherence, retention, and other Patient FIND use cases.
• Guide AI/ML teams on feature engineering, model input design, validation, monitoring, and scalable model-enablement practices.
• Provide technical leadership on tradeoffs involving model performance, governance, data quality, explainability, and downstream activation.

Signal Readiness, Governance Enablement and Data Quality

• Own the signal readiness framework for Patient FIND data assets and platform flows.
• Define and implement quality, governance, metadata, lineage, access, and consumption standards embedded within Patient FIND data products and workflows.
• Lead resolution of cross-functional data, platform, privacy, compliance, governance, and access issues.

Deployment, Consumption and Measurement

• Define and own the deployment and measurement framework for Patient FIND outputs across CRM, field, marketing, BI, medical, omnichannel, and leadership workflows.
• Own the measurement data layer that connects patient identification, engagement, outcomes, and model refinement into a closed-loop learning capability.
• Ensure outputs are consumable, measurable, scalable, and actionable while providing leadership visibility into capability maturity, constraints, and investment opportunities.

Cross-Functional Technical Leadership

• Serve as the senior technical operating lead for the Patient FIND data product and analytics engineering capability.
• Drive alignment on technical priorities, shared definitions, quality expectations, governance requirements, and implementation approaches across Patient FIND stakeholders.
• Influence senior stakeholders and technical teams by translating complex technical and analytical tradeoffs into clear options, recommendations, and decision implications.
• Represent data product, analytics engineering, and technical readiness in roadmap, governance, investment, prioritization, and operating model discussions.

Capability Building and Future People Leadership

• Help define the future operating model, organizational structure, and capability roadmap required to scale Patient FIND across the enterprise.
• Serve as a player-coach, mentoring technical contributors and establishing standards, review practices, documentation, and delivery disciplines.
• Support future hiring, talent development, and succession planning for data product, analytics engineering, and AI/ML capabilities.

Requirements

• Bachelor’s degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, Bioinformatics, Health Informatics, Epidemiology, Life Sciences, or related quantitative field.
• 8+ years of progressive experience in data science, analytics engineering, healthcare analytics, data product development, life sciences analytics, or related technical leadership roles.
• Demonstrated experience leading complex, cross-functional data or analytics initiatives from ambiguous business need through technical design, delivery, governance, and downstream adoption.
• Strong SQL and Python capability, with experience transforming, profiling, validating, and analyzing large-scale healthcare or life sciences data.
• Experience developing reusable analytical datasets, feature logic, model inputs, data products, measurement layers, and production-grade analytical workflows.
• Experience working with healthcare or pharmaceutical data sources such as claims, EHR/EMR, lab data, Rx data, CRM, specialty pharmacy, hub/patient services, digital engagement, or real-world data.
• Demonstrated ability to set technical direction, influence senior stakeholders, and align matrixed teams around reusable data and analytics patterns.
• Strong understanding of data quality, metadata, reproducibility, lineage, access controls, privacy considerations, governed analytics, and AI/ML enablement.
• Proven ability to translate ambiguous strategic questions into structured technical requirements, build plans, tradeoffs, and recommendations.
• Strong executive communication skills, including the ability to explain data logic, technical risks, delivery options, and business implications to technical and non-technical audiences.
• Experience mentoring, guiding, or providing technical direction to data scientists, analytics engineers, contractors, or matrixed technical contributors.
• Experience in pharma, biotech, rare disease, specialty pharmacy, commercial analytics, medical analytics, RWD, HEOR, or patient identification and patient finding.
• Experience with Databricks, Snowflake, Azure, AWS, Dataiku, dbt, Airflow, Git, Power BI, Tableau, or similar modern data and analytics platforms.
• Familiarity with MLOps, model monitoring, CI/CD, API based data products, or production grade analytics workflows.
• Experience supporting commercial pharma use cases such as HCP targeting, patient finding, patient journey analytics, adherence, treatment switching, territory or account prioritization, launch analytics, or field effectiveness.
• Experience working in a highly regulated environment with privacy, compliance, legal, medical, and governance stakeholders.
• Familiarity with rare disease commercialization, diagnostic odyssey, claims or EHR signal detection, HCP network mapping, or patient activation pathways.
• Ability to work across technical teams and business teams, especially where ownership, definitions, and decision rights are still being clarified.