{"id":724190,"url":"https://alion.io/job/probablygenetic-senior-data-scientist","title":"Senior Data Scientist","company":{"id":685488,"name":"Probably Genetic","domain":"probablygenetic.com","url":"https://alion.io/company/probablygenetic","size_band":"11-50","is_staffing_agency":false,"is_intermediary":false,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":81,"open_postings":4,"ghost_share":0,"stale_share":0.75,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-09-23T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":180000,"max":230000,"currency":"USD","period":"year","gross":null,"usd_annual":230000},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Databricks","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"NLP","optional":false},{"name":"NumPy","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"Synthetic Data","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-06-03T23:35:36Z","employer_posted_date":"2026-06-03","last_verified_at":"2026-09-24T00:25:34Z","board_verified":true,"closed_at":null,"days_open":112,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":111},"description":"About Probably Genetic\nProbably Genetic is changing the lives of patients living with severe, complex diseases. Our data platform is used by drug developers and patient advocacy groups to develop and launch treatments for these patients. Our technology discovers undiagnosed patients online, analyzes their disease state using machine learning and at-home testing, and enables compliant communication with patients. In doing so, we help patients access diagnoses, clinical trials, and treatments as early as possible.\nWe are a tight-knit group of hard-working, ambitious problem solvers united by a mission greater than ourselves. We do well by doing right by patients. We are developing some of the most cutting-edge solutions in healthcare, and our roadmap is packed with innovations in bioinformatics, AI, and drug development. We have built a lean, all-star team to help us bring our vision to life, and we want you to be a part of it.\nProbably Genetic has raised multiple rounds of funding from Silicon Valley’s best investors, including Threshold, Khosla, and Y Combinator, and offer competitive salaries, comprehensive benefits, and meaningful early stage equity.\nAbout the role\nWe are looking for a Senior Data Scientist who will own some of the most consequential diagnostic AI in rare disease: building, validating, and operationalizing the models that help us find and diagnose patients who have never had a name for their disease, powering the analytical rigor behind our testing programs, and shaping how we use data to make smarter product decisions.\nWhat you will do\nOwn 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\n\nRun prospective testing experiments: apply diagnostic models to undiagnosed patients, coordinate testing, and track outcomes to continuously improve model performance\n\nBuild and maintain PG's synthetic patient data pipeline, a critical deliverable for our research programs, and key input to our own model development lifecycle\n\nOptimize 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\n\nOwn API usage and cost optimization across PG's AI stack, including prompt engineering, model evaluation, and ongoing performance monitoring\n\nConduct ad hoc strategic analyses that inform product prioritization, causality assessment, and generate customer-facing program insights\n\nEstablish MLOps infrastructure: model monitoring, drift detection, API observability, and lightweight but durable operational processes\n\nHave the freedom to conduct blue sky research initiatives aimed at creating value from our data\n\nWork with Data Engineering to build a robust, scalable data foundation that supports all of the above\n\nWho you are\nWe are looking for a few specific things that will help you succeed in this role:\n7+ years of experience in data science, machine learning engineering, or a closely related field\n\nStrong Python proficiency and fluency across the core data science stack: pandas, NumPy, scikit-learn, PySpark, and SQL\n\nDemonstrated end-to-end ML experience: you have taken models from problem definition through feature engineering, validation, deployment, and monitoring in a production environment\n\nExperience with NLP techniques and applying language models to real-world problems\n\nComfort with prompt engineering and evaluating external AI API performance (e.g., OpenAI)\n\nA 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\n\nStrong analytical communication skills - you can translate complex model outputs and data findings into clear, actionable narratives for technical and non-technical audiences alike\n\nSome things that are not required, but you will learn on the job:\nExperience with Databricks or similar lakehouse/ML platform environments\n\nFamiliarity with synthetic data generation techniques\n\nDomain knowledge in healthcare, rare disease, genomics, or clinical research\n\nExperience with MLOps tooling and building observability infrastructure from scratch\n\nExposure to biopharma or insurance analytics use cases\n\nAs with all new hires at Probably Genetic, you will also need to be:\nA good person. We work with some of the most marginalized populations on the planet and empathy is key\n\nPatient-focused and motivated to have a lasting, positive impact on humanity\n\nComfortable in a fast-paced, often ambiguous environment with rapid change\n\nAction-oriented and excited to build a company from the ground up\n\nThe salary range for this role is $180,000-$230,000 annually. Actual compensation offered will depend on several factors including but not limited to: work experience, education, skill level, and/or other business and organizational needs.\nWhat we offer at Probably Genetic:\nAn engaging and supportive team all on a mission to improve lives\n\nFair and equitable compensation with competitive early-stage equity grants\n\nGenerous Flexible Time off policy, that we actually use\n\nParental Leave Benefits (12 weeks for both birthing and non-birthing)\n\nHybrid, flexible work with high-trust and autonomy\n\nA bright, inviting, pet-friendly office in Downtown SF near transit\n\nCompany-sponsored team lunch every Thursday\n\nA “work from anywhere” policy, up to 4 weeks a year\n\nRegular team retreats in exciting destinations\n\nHealth Benefits including medical, dental, vision, therapy, FSA, and 401k\n\nAnd so much more!\n\nProbably Genetic is committed to fostering a welcoming and inclusive work environment for people of all genders, sexuality, ethnicity, socioeconomic background and life experiences. We urge candidates of all backgrounds to apply. If you require specific accommodations as you interview or consider working with us, please let us know.","description_format":"text","description_chars":5996,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["401k plan","Equity","Flexible schedule","Flexible time off","Parental leave"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Health Care","Diagnostics","Molecular Diagnostics"],"lifecycle":[{"event":"open","at":"2026-09-11T07:56:41Z"}],"liveness":{"score":7,"band":"cold","label":"Long shot","p_open":1,"p_active":0.243,"p_room":0.28,"age_days":111,"expected_fill_days":30,"reasons":["conf:0","win:tail","crowd:"],"computed_at":"2026-09-23T05:45:00Z"},"pay":{"stated_usd_annual":230000,"is_top_pay":true},"html_url":"https://alion.io/job/probablygenetic-senior-data-scientist","json_url":"https://alion.io/job/probablygenetic-senior-data-scientist.json","meta":{"generated_at":"2026-09-24T00:32:26Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers"}}