Data Scientist
San Francisco · San Francisco, California, United States
- Pay
- Salary not listed in the saved posting
- Work setup
On-site — work setup source
Location type: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Engineering — team source
Department: Engineering
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Will you require work sponsorship now and/or in the future?
From the employer’s application form
What you’ll work on
Full postingDefine north-star and feature-level metrics for our ranking, interview analytics, and payouts systems.
Design/run A/B tests and quasi-experiments; turn results into product decisions the same week.
Build source-of-truth dashboards and lightweight data models so teams can self-serve answers.
From the employer’s posting
In your first year you’ll ship analyses and experiments that move core product metrics, match quality, time-to-hire, candidate experience, and revenue. You’ll: Define north-star and feature-level metrics for our ranking, interview analytics, and payouts systems. Design/run A/B tests and quasi-experiments; turn results into product decisions the same week.
Define north-star and feature-level metrics for our ranking, interview analytics, and payouts systems. Design/run A/B tests and quasi-experiments; turn results into product decisions the same week. Build source-of-truth dashboards and lightweight data models so teams can self-serve answers.
Design/run A/B tests and quasi-experiments; turn results into product decisions the same week. Build source-of-truth dashboards and lightweight data models so teams can self-serve answers. Instrument events with engineers; improve data quality and latency from ingestion to insight.
What you’ll bring
All qualificationsCore experience
- 0–2 years in data science/analytics or similar; BS/BA in a quantitative field (or equivalent work).
- Strong SQL; Python for analysis; comfort with experiment design and causal thinking.
Qualification wording
0–2 years in data science/analytics or similar; BS/BA in a quantitative field (or equivalent work).
Strong SQL; Python for analysis; comfort with experiment design and causal thinking.
Tools in this posting
- Python
- SQL
- Databricks
- dbt
- Looker
Source — Tool mentions in context
You’ll thrive here if You have solid fundamentals (statistics, SQL, Python) and projects you’re proud to demo. You iterate fast, frame the question, test, and ship in day, and care as much about clarity of communication as you do about p-values. Curiosity about LLM evaluation, retrieval, and ranking is a bonus; you’ll learn alongside folks who’ve shipped at Jane Street, Citadel, Databricks, and Stripe. Qualifications
- 0–2 years in data science/analytics or similar; BS/BA in a quantitative field (or equivalent work). - Strong SQL; Python for analysis; comfort with experiment design and causal thinking. - Communicates crisply with engineers, PMs, and leadership; turns analysis into action.
- Communicates crisply with engineers, PMs, and leadership; turns analysis into action. - Nice-to-haves: dbt, dashboarding (Hex/Mode/Looker), marketplace or search/recommendation metrics, LLM/agent evaluation. Benefits
Benefits in the posting
Full benefits wording- Bi-annual performance bonus structure
- Generous equity grant vested over 4 years
- Up to $15k Relocation bonus
- $10K housing bonus (if you live within 0.5 miles of our office)
- $1.5K monthly stipend for meals
- Free Equinox membership
- $200 monthly personal wellness reimbursement
- Health, Dental, Vision insurance
From the employer’s posting.
About Mercor
Mercor's mission is to organize human intelligence to power the AI economy.
In the employer’s words · Read in context · Company website ↗
Job description
About Mercor
Mercor's mission is to organize human intelligence to power the AI economy. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development. Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $3 million a day.
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.
What you’ll do
In your first year you’ll ship analyses and experiments that move core product metrics, match quality, time-to-hire, candidate experience, and revenue. You’ll:
Define north-star and feature-level metrics for our ranking, interview analytics, and payouts systems.
Design/run A/B tests and quasi-experiments; turn results into product decisions the same week.
Build source-of-truth dashboards and lightweight data models so teams can self-serve answers.
Instrument events with engineers; improve data quality and latency from ingestion to insight.
Prototype quick models (from baselines to gradient boosting) to improve matching and scoring.
Help evaluate LLM-powered agents: design rubrics, human-in-the-loop studies, and guardrail canaries.
You’ll thrive here if
You have solid fundamentals (statistics, SQL, Python) and projects you’re proud to demo. You iterate fast, frame the question, test, and ship in day, and care as much about clarity of communication as you do about p-values. Curiosity about LLM evaluation, retrieval, and ranking is a bonus; you’ll learn alongside folks who’ve shipped at Jane Street, Citadel, Databricks, and Stripe.
Qualifications
0–2 years in data science/analytics or similar; BS/BA in a quantitative field (or equivalent work).
Strong SQL; Python for analysis; comfort with experiment design and causal thinking.
Communicates crisply with engineers, PMs, and leadership; turns analysis into action.
Nice-to-haves: dbt, dashboarding (Hex/Mode/Looker), marketplace or search/recommendation metrics, LLM/agent evaluation.
Benefits
Bi-annual performance bonus structure
Generous equity grant vested over 4 years
Up to $15k Relocation bonus
$10K housing bonus (if you live within 0.5 miles of our office)
$1.5K monthly stipend for meals
Free Equinox membership
$200 monthly laundry reimbursement
$200 monthly personal wellness reimbursement
Health, Dental, Vision insurance
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.
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Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
San Francisco, California, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Jun 2, 2026
- Recorded sightings
- 26
- Last seen by us
- Sep 30, 2026
- Employer says posted
- Aug 30, 2025
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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