Senior Data Scientist, BillionToOne

• 3+ years of experience in a data science, analytics engineering, or related data role. More experience is welcome
• Strong proficiency in SQL and Python (or R) for data manipulation and analysis
• Comfort working with messy, disparate data sources and the judgment to know when to clean, when to re-model, and when to push upstream
• Experience working with clinical, healthcare, or other regulated data
• Hands-on experience using AI tools to enhance your work, and an interest in helping others do the same
• Excellent communication skills and the ability to partner directly with non-technical stakeholders to scope problems and deliver useful answers
• A strong sense of ownership: you are comfortable working directly with stakeholders and treat data quality and stakeholder outcomes as part of your job

Desirable

• We are looking for a Senior Data Scientist to join our Prenatal data team
• At BillionToOne, our data scientists are full-stack: we own the entire analytics value chain
• That means wearing a data engineering hat to land data into our central warehouse, an analytics engineering hat to model, document, and test it, and a data science hat to analyze it, build dashboards, and deliver insights that drive decisions across the company
• This is a high-impact, high-autonomy role
• You will work directly with stakeholders across the business — commercial teams, lab operations, clinical and quality teams, bioinformatics, and executive leadership — owning those relationships end-to-end
• AI is woven through how we work: you will use it daily to accelerate your own analyses and engineering, build HIPAA-compliant AI-powered analysis workflows for the team, and help colleagues across the organization adopt AI to do their best work
• Own the full analytics stack for Prenatal: ingest data from disparate sources into our central data warehouse, build clean and well-tested data models, and deliver analyses, dashboards, and tooling that stakeholders can use directly
• Partner with stakeholders across the business to answer high-stakes questions with data — for example, helping the lab improve turnaround time, helping sales identify at-risk accounts and new business opportunities, supporting clinical affairs with data on samples and outcomes, supporting business metrics around new product launches, and informing executive decisions on growth and strategy
• Build and maintain the central analytical data warehouse that aggregates data from across the organization, while partnering with teams who own their own operational systems (e.g., Clarity, bioinformatics pipelines)
• Use AI tools to accelerate your own work, build HIPAA-compliant AI-powered analysis workflows, and help colleagues across the company adopt AI to improve their productivity
• Develop and maintain Tableau dashboards and self-serve analytics that turn data into action for clinical, commercial, and operational teams