Hiring Now
Data Scientist Jobs Hiring Now (September 2026)
Data scientists turn data into decisions. The role spans statistical modeling, experimentation, machine learning, and partnership with product and business teams to drive measurable impact.
Data Scientist market snapshot
Live from PrismCV's job catalog. Salaries reflect postings that publish a range; remote share excludes postings without a location tag.
Data scientist postings in 2026 describe at least three distinct jobs sharing one title. Product data science is experimentation and decision support embedded with product teams: the work is tests, metrics, and analyses that change roadmaps. Modeling roles ship models that production systems consume: ranking, risk, forecasting, personalization. And a growing slice is generative-AI-adjacent: evaluation, retrieval quality, and data work behind LLM features. Read the responsibilities and the team description to identify which job a posting actually is, because the interview loops differ sharply.
Stack expectations are stable: Python and strong SQL universally; the experimentation stack (a testing platform, causal-inference literacy) for product roles; the modeling stack (gradient boosting as table stakes, deep learning where relevant, an orchestration/deployment story) for ML-leaning roles. dbt and warehouse fluency appear in a growing share of postings as the analytics-engineering boundary blurs. LLM-evaluation experience has moved from novelty to named requirement in many product-DS postings.
The market rewards legible specialization at senior levels. Generalist DS postings concentrate at smaller companies hiring their first or second data scientist: broad, high-ownership roles that suit people who like ambiguity. Larger companies hire into lanes and interview accordingly. Mid-career candidates do best applying to the lane their strongest evidence supports rather than spraying one resume at all three.
Posting patterns worth noting: "data scientist" roles that are mostly dashboarding are analyst roles titled up. Fine work, but know what you are applying to. Roles that require the full spectrum (experimentation plus modeling plus production deployment plus stakeholder management) at mid-level compensation are describing two or three jobs; ask which one the team actually needs in the first call.
Use the listings below as your feed. PrismCV crawls the major boards and de-duplicates across them. The live salary data above reflects what current postings advertise for this title, and the ATS Checker scores your resume against any posting before you apply, which is useful in a field where the same title hides different keyword sets.
Companies hiring data scientists now
The five companies with the most active openings in this role today.
Latest open positions
Crawled across major job boards. Click through for full details, salary, and the apply link.
Data Scientist - Music Promotion
Spotify · New York, NY · Remote
Staff Data Scientist (Quantitative Researcher)
Robinhood · New York, NY
Senior Data Scientist, Organic Growth
Chime · San Francisco, CA, USA
Principal Data Scientist, Detection
Cloudflare · Hybrid
Data Scientist, Community Support (Inference)
Airbnb · Remote - USA · Remote
Senior Data Scientist, Risk and Support
Block (Square) · Seattle, WA, United States of America
Senior Data Scientist, Risk and Support
Block (Square) · Bay Area, CA, United States of America
Applied Scientist/Machine Learning Engineer Gaia
Wayve · London
Data Scientist
Waymo · Mountain View, California, United States
Staff Data Scientist - Experience
Spotify · Stockholm
Senior Data Scientist
Lucid Motors · Phoenix, AZ
Data Scientist
Lyft · Seattle, WA
Full-Stack Data Scientist, Hardware Reliability (Starlink)
SpaceX · Bastrop, TX
Data Scientist (Analytics)
Baseten · San Francisco · Remote
Senior Fraud Data Scientist (Credit Card)
Gemini · New York, New York; Miami, Florida; Remote (USA) · Remote
Senior Applied Scientist - AI Platform
Datadog · Paris, France
Staff Data Scientist
Mercury · San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
Senior Data Scientist
Mercury · San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
Staff Applied Scientist
Braze · San Francisco
Staff Applied Scientist
Braze · Chicago
Staff Applied Scientist
Braze · Austin
Staff Applied Scientist
Braze · New York City
Data Scientist - Algorithms, Mapping
Lyft · Toronto, Canada
Data Scientist, Risk
Gusto · San Francisco, CA - Hybrid
Senior Data Scientist
Sonatype · Toronto - Remote · Remote
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Scoring methodologyFrequently asked questions
The function is shifting more than shrinking. Routine analysis is increasingly automated, which raises the premium on what remains: experiment design, causal reasoning, metric judgment, and evaluating AI systems themselves. LLM-evaluation and AI-measurement skills appear in a growing share of postings; data scientists who can measure whether AI features actually work are in demand precisely because of the AI wave.
Both are healthy with different shapes. ML-engineering-adjacent roles command a premium where production skills are scarce; product DS has more openings at companies whose core asset is decision-making rather than models. Pick by what you want to own, decisions or systems, and the evidence trail you can show; that fit converts better than chasing either market.
Ask what decision the team changed in the last quarter (a real answer means influence; silence means dashboards), how experiments get reviewed before launch, and where DS reports (product, engineering, or a centralized org), since that placement determines whether you advise or own. Also ask who maintains the pipelines you would depend on.
Compare your Data Scientist resume with a job description
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Scoring methodology and limitationsRun Free ATS Check