Sr. Director, Data Science, Patient Identification San Francisco, CA, 94118
Description:
Mavericks Wanted When was the last time you achieved the impossible? If that thought feels overwhelming, you might want to pause here, but if it sparks excitement...read on In 2015, we pioneered a "moneyball for biotech" approach, pooling projects and promising early-stage research from academia together under one financial umbrella to reduce risk and unleash innovation. This model allows science and small teams of experts to lead the way. We build bridges to groundbreaking advancements in rare disease, and develop life-changing medicines for patients with unmet needs as fast as humanly possible. Together we define white space, push boundaries and empower people to solve problems. If you're someone who defies convention, join us and work alongside some of the most respected minds in the industry. Together, we'll ask "why not?" and help reengineer the future of biopharma.
What You'll Do:
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.
Responsibilities:- Strategic Data Science Leadership
- 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 (use of data and data science work across the organization), precision, urgency, and patient impact
- Advanced Analytics & Machine Learning
- 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.
