Data Science Manager

Prolific•New York, NY

About The Position

Prolific is not just another player in the AI space—we are the architects of the human data infrastructure that's reshaping the landscape of AI development. In a world where foundational AI technologies are increasingly commoditized, it's the quality and diversity of human-generated data that truly differentiates products and models. The Role Prolific for AI is a high-growth, greenfield vertical building the infrastructure behind human-aligned AI. As Data Science Manager, you'll build and lead the data science and analytics function for this vertical - setting strategy, hiring the team, and partnering with commercial, product, and ops stakeholders to drive measurable impact. You'll define what great looks like, then build the team and systems to deliver it.

Requirements

Proven track record leading data science or analytics teams — you've hired, developed, and held a high technical bar
Technically deep enough to set direction, review work critically, and earn credibility with strong ICs — not just manage process
Expertise in experimentation and causal inference; you know the difference between a well-designed study and a convincing-looking one
Ability to translate ambiguous, high-stakes business problems into structured analytical work
Strong stakeholder influence — you can align Product, Eng, Ops, and Commercial without direct authority

Nice To Haves

experience with AI data pipelines, RLHF, or human-in-the-loop evaluation systems

Responsibilities

Build & Lead the Team
Hire, develop, and retain a high-performing team of Data Scientists and Analysts
Set clear expectations for technical quality — rigorous causal inference, well-designed experiments, principled modelling — and coach the team to meet them
Define ways of working, prioritisation, and how the team interfaces with commercial and product stakeholders
Drive Commercial Growth through Data
Ensure your team delivers analytics that fuel the Prolific for AI Sales and Ops functions: pipeline health, forecasting, customer health, and retention signals
Act as a senior data thought partner to commercial leadership — translating business questions into analytical problems and outcomes into decisions
Own the Experimentation Standard
Set and hold the bar for how your team designs, runs, and interprets experiments — going beyond basic A/B testing toward rigorous causal inference and algorithmic work
Partner with Product to make experimentation a core capability across the vertical, not just a tool
Ensure Data Quality at Scale
Lead your team to build scalable frameworks that guarantee high-quality AI training and evaluation data for Prolific's frontier lab partners
Establish governance: clear rules, repeatable checks, and shared standards that Product and Engineering can build against
Be hands-on in the early phase — contributing technically where needed — then transition to technical oversight and mentorship as the team matures