Senior Data Scientist

Probably Genetic

Senior Data Scientist at Probably Genetic building predictive diagnostic AI models for rare diseases. Collaborating with teams to enhance patient diagnosis and improve healthcare solutions.

Posted 6/4/2026full-timeSan Francisco • California • 🇺🇸 United StatesSenior💰 $180,000 - $230,000 per yearWebsite

Tech Stack

Tools & technologies

NumpyPandasPySparkPythonScikit-LearnSQL

About the role

Key responsibilities & impact

Own the end-to-end development, validation, and operationalization of PG's predictive diagnostic AI models — from feature engineering through production deployment – that power program eligibility decisions and clinical decisions for patients
Run prospective testing experiments: apply diagnostic models to undiagnosed patients, coordinate testing, and track outcomes to continuously improve model performance
Build and maintain PG's synthetic patient data pipeline, a critical deliverable for our research programs, and key input to our own model development lifecycle
Optimize our patient intake experience using NLP and multimodal data analysis to determine which questions to ask, in what order, to maximize data quality and conversion
Own API usage and cost optimization across PG's AI stack, including prompt engineering, model evaluation, and ongoing performance monitoring
Conduct ad hoc strategic analyses that inform product prioritization, causality assessment, and generate customer-facing program insights
Establish MLOps infrastructure: model monitoring, drift detection, API observability, and lightweight but durable operational processes
Have the freedom to conduct blue sky research initiatives aimed at creating value from our data
Work with Data Engineering to build a robust, scalable data foundation that supports all of the above

Requirements

What you’ll need

7+ years of experience in data science, machine learning engineering, or a closely related field
Strong Python proficiency and fluency across the core data science stack: pandas, NumPy, scikit-learn, PySpark, and SQL
Demonstrated end-to-end ML experience: you have taken models from problem definition through feature engineering, validation, deployment, and monitoring in a production environment
Experience with NLP techniques and applying language models to real-world problems
Comfort with prompt engineering and evaluating external AI API performance (e.g., OpenAI)
A track record of operating with high ownership in lean, fast-moving environments where you have had to build structure as much as execute within it
Strong analytical communication skills — you can translate complex model outputs and data findings into clear, actionable narratives for technical and non-technical audiences alike.

Benefits

Comp & perks

An engaging and supportive team all on a mission to improve lives
Fair and equitable compensation with competitive early-stage equity grants
Generous Flexible Time off policy, that we actually use
Parental Leave Benefits (12 weeks for both birthing and non-birthing)
Hybrid, flexible work with high-trust and autonomy
A bright, inviting, pet-friendly office in Downtown SF near transit
A “work from anywhere” policy, up to 4 weeks a year
Regular team retreats in exciting destinations
Health Benefits including medical, dental, vision, therapy, FSA, and 401k
And so much more!

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Hard Skills & Tools

PythonpandasNumPyscikit-learnPySparkSQLNLPmodel deploymentfeature engineeringMLOps

Soft Skills

analytical communicationownershipproblem-solvingcollaborationadaptabilitystrategic analysisnarrative translationexecutionresearch initiativedata-driven decision making