Member of Technical Staff (Data Scientist)
Perplexity - San Francisco, California, United States
Posted Feb 20, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified
- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Not verified
- Relocation assistance
- Not verified
- Childcare support
- Not verified
- Learning budget
- Not verified
- Verification
- Not verified
- Salary
- Not verified
- 401(k) match
- Not verified
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Market context
- U.S. role benchmark (BLS OEWS)
- $111,944 U.S. median for this role
- Projected growth (BLS Employment Projections)
- +13.7% - Much faster than average
Matched to SOC 15-1252 - Data and ML aggregate by role bucket.
Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.
Role
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Company
- Company stage
- Growth-stage From the posting source checked Jun 20, 2026
Application
- Cover letter
- Not verified
- Assessment
- Not verified
- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Member of Technical Staff (Data Scientist) San Francisco, California, United States Perplexity is AI for people who expect more. This role brings that same standard to how our data team works - with AI at the center of everything we do. We're looking for someone who's been a great data scientist, analytics engineer, or data engineer - the kind of person who knows which metric actually matters, who can design an A/B test that answers the real question, who's gone deep on a data model because something didn't add up - and who has decided that the highest-leverage thing they can do next is build AI systems that fundamentally change how data science gets done . Not another text-to-SQL bot. Not another dashboard. You'll build AI agents that conduct full analyses autonomously - forming hypotheses, writing and running queries, interpreting results, and drafting recommendations. You'll make the entire data warehouse AI-readable so any system can query it accurately. You'll create self-healing pipelines that detect and fix data issues before anyone notices. You'll build the infrastructure that turns a small data team into one that operates at 10x its size. You'll join a data team that's already using AI across its workflows - but we know there's a much bigger opportunity ahead. We have buy-in from leadership to make it happen. Now we're building a team dedicated to taking what we've started and turning it into something world-class: scalable systems, new tools, and an AI-native way of working that doesn't just
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