Talent Intelligence & Analytics Manager
At a glance
Manager-level Data Analysis & BI role at Mercor. San Francisco · full-time · $140,000–$180,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Map where frontier labs, major technology companies, and competitors recruit AI talent, how their teams are organized, and how they pitch offers
- Review hiring-funnel measures such as stage conversion, time in stage, source yield, and hire quality, then recommend changes
- Create dashboards that show recruiting leaders current pipeline health and hiring capacity
- Research AI talent supply and pay trends, maintain compensation comparisons across roles and markets, and present findings to leaders
- Answer market and pipeline questions from recruiters and business leaders across GTM, Applied AI, and Operations
What you bring
- At least five years in people analytics, talent intelligence, or recruiting analytics, ideally in a high-growth tech or AI setting
- Strong SQL and data modeling skills, plus experience building dashboards with tools such as Hex, Looker, or Tableau
- Ability to turn imperfect data into a clear recommendation and confidently explain data-backed conclusions to recruiters and leaders
Who this fits
This role suits someone who wants to make talent-market and recruiting-funnel evidence useful for hiring decisions. You’ll work in person five days a week in San Francisco, New York City, or London. The stated annual pay range is $140,000 to $180,000.
From the employer
About Mercor
Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.
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.
About the Role
As a Talent Intelligence & Analytics Manager at Mercor, you'll be the person who knows the AI talent market better than anyone else on the team: where competitors are finding talent, how compensation is trending, and what it actually takes to win a candidate in this market. You'll build the data and research layer underneath all of Mercor's recruiting - GTM, Applied AI, Operations, and beyond - turning market signal and funnel data into decisions our recruiters and leadership can act on.
What You'll Do
Track the competitive AI talent landscape: where frontier labs, Mag 7 companies, and direct competitors are sourcing talent, how their teams are structured, and how they're positioning offers
Analyze Mercor's own hiring funnel: pass-through rates, time-in-stage, source yield, and quality of hire, and turn that into recommendations recruiters and leadership can act on
Build dashboards and reporting that give recruiting leadership a real-time read on pipeline health and hiring capacity
Act as the analytics expert for Talent Acquisition, informing strategic decision making across the recruiting funnel
Partner with business leadership as well as recruiters across GTM, Applied AI, and Operations to answer their specific market and pipeline questions
Run research projects on talent-market trends: where the best AI talent is coming from, how compensation structures are evolving, and what's changing in how competitors hire
Build and maintain compensation benchmarking across roles and markets, keeping Mercor's offers competitive as the AI talent market shifts
Present findings directly to recruiting and company leadership, translating data into a clear point of view
What We're Looking For
5+ years of experience in people analytics, talent intelligence, or recruiting analytics, ideally at a high-growth tech or AI company
Strong SQL and data modeling skills; comfort building dashboards in tools like Hex, Looker, or Tableau
A genuine interest in the AI talent market: who's hiring, where they're finding people, how comp is trending, and what that means for Mercor's competitiveness
Ability to turn messy data into a clear narrative and a clear recommendation, not just a report
Strong communication skills; able to present data-backed points of view to recruiters and leadership with confidence
High motor, outcome-oriented approach; Mercor is in hypergrowth, and this role's insights directly shape hiring decisions across the company
Familiarity with Ashby or ability to quickly adopt new tools and systems
Nice to Haves
Experience in a strategy, market research, or competitive intelligence role prior to moving into talent/people analytics
Interest in the human data / AGI space
Experience building compensation benchmarking models or market-pay studies
Comfort supporting multiple recruiting functions (GTM, Applied AI, Operations) at once
Ideal Qualities
Agility / Adaptability - ability to move fast, pivot with business shifts, and maintain best-in-class outcomes
Operational Rigor - ability to bring order to an unstructured environment
Growth Mindset - You don't need to be an expert on AI, but you do need a strong desire to learn in a rapidly evolving, frontier industry
Commitment to the Outcome - Ownership mentality; will hold yourself accountable to an extremely high standard of work
Love for the Craft - genuine enthusiasm for building a best-in-class talent function
Data Analysis & BI work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
Data Analysis & BI$140k+
Find me workBy the team behind dataroles.