Sr. Director, Data Science, Patient Identification

Executive Staff Recruiters / ESR Healthcare; San Francisco (CA); On-site; USD 250,000 - 350,000; Full time

Job summary

BrigeBio seeks a Sr. Director of Data Science for Patient Identification in San Francisco, CA. You will lead the data science function, shape strategy, and drive translational analytics across rare disease programs.

You will develop AI/ML approaches and leverage real-world data to identify undiagnosed patients, accelerate diagnosis, and inform decision making that improves patient outcomes.

Qualifications

• Leadership of a data science function focused on patient identification and provider targeting.
• Design and development of AI/ML models using real-world data.
• Apply NLP/LLM to extract signals from unstructured EMR data.

Responsibilities

• Spearhead a high-performing data science function focused on patient identification and provider targeting.
• Define vision, priorities, and success metrics for data science initiatives across programs.
• Architect scalable analytical solutions using real-world data including claims, EMR, genomics, and lab data.

Skills

Data science leadership

AI/ML modeling

RWD data sources

NLP / LLM techniques

Experimentation design

Model monitoring & deployment

Job description

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.