Hiring Now
Data Scientist Jobs Hiring Now (June 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.
Staff Data Scientist, ML (Credit Risk)
Robinhood · Menlo Park, CA; New York, NY; Washington, DC
Data Scientist, Marketing
Figma · San Francisco, CA • New York, NY • United States
Marketing Data Scientist
CircleCI · Remote, US · Remote
Staff Data Scientist
Udemy · Denver, CO
Staff Data Scientist
Udemy · Austin, TX
Forward-Deployed Data Scientist
Braze · Tokyo
Data Scientist
Why Hiring · Canada, · Remote
Senior Data Scientist, Causal Inference
Lyft · Seattle, WA
Senior Data Scientist, Causal Inference
Lyft · New York, NY
Senior Data Scientist, Causal Inference
Lyft · San Francisco, CA
Staff Data Scientist, Ads Product
Pinterest · San Francisco, CA, US; Remote, US · Remote
Senior Data Scientist
Coursera · Canada
Senior Data Scientist, Trust & Safety
Chime · San Francisco, CA, USA
Senior Data Scientist, Spending
Chime · San Francisco, CA, USA
Senior Data Scientist, Growth Product
Chime · San Francisco, CA, USA
Data Scientist, Growth Product
Chime · San Francisco, CA, USA
Principal Data Scientist - Agent Builder
Elastic · United Kingdom
Lead Machine Learning Engineer / Applied Scientist
Upwork · Toronto, Ontario, Canada
Staff Product Data Scientist, Expansion
Waymo · Mountain View, CA, USA; San Francisco, CA, USA
Data Scientist
YO HR Consultancy · Remote · Remote
Data Scientist III
ZoomInfo · Toronto, Ontario, Canada
Data Scientist II
ZoomInfo · Toronto, Ontario, Canada
Data Scientist, Autonomy Behavior Monitoring
Zoox · Foster City, CA
Data Scientist, Economic Insights & Research
Stripe · US
Data Scientist, Behavior Evaluation
Zoox · Foster City, CA
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Frequently 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.
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