Sr. Director, Data Science, Patient Identification

BridgeBio Pharma-posted 2 months ago

Full-time • Senior

Hybrid • San Francisco, CA

501-1,000 employees

Chemical Manufacturing

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Maverick wanted! We're seeking a Sr. Director, Data Science, Patient Identification who thrives at the frontier of machine learning/statistical modelling, healthcare data, and translational analytics. You'll develop approaches and models (AI/ML/traditional statistics) that find patients, detect disease patterns that are indicative of an undiagnosed rare disease, shape data strategies, and feed targeting engines that directly change patients' and families' lives. In this role, you'll shape and lead data-driven strategies to uncover undiagnosed patients, accelerate diagnosis, and drive smarter decisions across our rare disease portfolio. If you're passionate about using data science to drive tangible patient outcomes, this is where you belong.

Spearhead a high-performing data science function focused on patient identification and provider targeting
Identify, source, and integrate (tokenized) data assets in the pursuit of finding rare disease patients and treating HCPs across the portfolio for BrigeBio companies
Define the vision, priorities, and key success metrics for data science initiatives across multiple rare disease programs
Architect scalable analytical solutions using RWD (claims, EHR, genomics, lab data, imaging, and registry sources)
Define the roadmap for AI/ML innovation, balancing cutting-edge research with production-grade reliability
Build and foster a collaborative, mission-driven culture grounded in an enterprise perspective
Design predictive models, algorithms, and patient finding tools using real-world data (claims, EMR, lab/genomics)
Apply NLP and LLM techniques to extract phenotypic signals from unstructured EMR data
Pioneer new methodologies in AI/ML for patient identification, leveraging subtle clinical and diagnostic patterns
Design and execute experiments with different approaches to patient finding
Build frameworks for model monitoring, retraining, and performance evaluation in real-world deployment environments
Design and deploy supervised and unsupervised models for patient finding, diagnostic acceleration, and disease progression prediction
Translate complex insights into actionable strategies for field execution, engagement planning, and clinical partnerships
Drive the development of robust data pipelines, governance frameworks, and scalable model-serving infrastructure
Evaluate and integrate third-party data (claims, genomics, HCP, diagnostic lab feeds) to enhance model accuracy and reach
Partner with outside vendors and internal resources to operationalize analytics solutions across BridgeBio's portfolio
Champion best practices in reproducibility, version control, and MLOps
Partner with Commercial, Medical Affairs, and Computational Genomics teams to integrate analytic insights into decision-making
Engage with KOLs and data partners to identify early clinical signals that inform algorithmic models
Establish program-level KPIs, dashboards, and reporting frameworks to track performance and continuously improve model accuracy
Ensure compliance with HIPAA, privacy, and ethical data governance standards
Manage external vendors and partnerships to expand analytic capabilities and accelerate delivery

10+ years of experience in data science or analytics within biotech/pharma; 3+ years in a leadership role
Proven expertise in real-world data (RWD) analytics, patient identification, and segmentation across multiple therapeutic areas
Experience with large-scale real-world data (claims, EMR/EHR, lab/genomics, registry, or wearable data)
Experience developing and deploying sophisticated ML/statistical models using large-scale health data
Deep expertise in building predictive and classification models using Python, R, SQL, TensorFlow, PyTorch, or equivalent tools
Strong understanding of feature engineering, model explainability, and ML pipeline automation
Proven success translating analytics into actionable strategies that drive measurable patient or business outcomes
Bachelor's degree in data science, computer science, statistics, or a related quantitative field
Experience in rare disease analytics or patient-finding programs that supported commercial launches or diagnostic initiatives

Advanced degree (PhD, MS, MPH) in data science, biostatistics, computer science, or related field
Familiarity with generative AI, LLMs, or graph-based learning applied to healthcare or biomedical data

Market leading compensation
401K with 100% employer match on first 3% & 50% on the next 2%
Employee stock purchase program
Pre-tax commuter benefits
Referral program with $2,500 award for hired referrals
Comprehensive health care with 100% premiums covered - no cost to you and dependents
Mental health support via Spring Health (6 therapy sessions & 6 coaching sessions)
Hybrid work model - employees have the autonomy in where and how they do their work
Unlimited flexible paid time off - take the time that you need
Paid parental leave - 4 months for birthing parents & 2 months for non-birthing parents
Flex spending accounts & company-provided group term life & disability
Subsidized lunch via Forkable on days worked from our office
Skill development and career paths through regular feedback, continuous education and professional development programs

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