Senior Data Scientist, Marketplace at Lyft
San Francisco, CA
$148,000–$185,000from the description
Jul 6, 2026
San Francisco, CA
Jul 20, 2026
What this job asks for AI summary
This role sits on a team responsible for real-time supply and demand signals and forecasts that drive automated marketplace decisions — including dynamic pricing and supply management — within a rideshare platform. Day-to-day work centers on building, evaluating, and shipping time series forecasting and machine learning models into production, alongside backtesting, live experiments, and monitoring infrastructure. It suits a data scientist with substantial hands-on ML modeling experience in large-scale or real-time production environments.
Senior level · 5+ years · San Francisco-Oakland-Berkeley, CA · Full-time
Posted 5 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 65 people in the San Francisco-Oakland-Berkeley, CA area plausibly meet what this posting asks for (data scientists). range 40–100
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $173,851 (middle half $133,298–$217,653). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (8)
The role sits at the boundary of Data Science (15-2051) and Software Development (15-1252): the JD explicitly requires writing production model code and collaborating on scaling algorithms in production, which is heavier engineering involvement than a typical DS role. 15-2051 was chosen as primary because the core work is designing, training, and evaluating ML/forecasting models.
The degree requirement lists M.S. or Ph.D. but explicitly allows 'related work experience' as an alternative, so no minimum degree is hard-gated.
The JD mentions 'modern ML libraries' without naming specific ones (e.g. scikit-learn, PyTorch, TensorFlow); these are captured generically as 'ML libraries' since no specific library is named as a gate.
SQL is not explicitly named but 'querying, aggregation, analysis' of data is listed as a hard requirement; SQL is the canonical tool for this and is implied by the production data environment described.
A/B testing is inferred from the explicit requirement to 'design and implement both simulated backtesting and live experiments; analyze experimental and observational data' — this is a firm requirement, not merely preferred.
'Real-time systems' and 'operations research' appear as context (real-time production settings described as 'ideal'; operations research listed as a qualifying degree field) and are marked preferred accordingly.
The posted salary range ($148,000–$185,000/year) is specific to the San Francisco area; the recruiter may share different ranges for other locations.
This is a hybrid role (3 days/week in-office: Mon/Wed/Thu) — not fully remote.
Read the full posting
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