Data Science Director

Meta•Menlo Park, CA

3d•$253,000 - $314,000

About The Position

We're looking for a seasoned analytics leader to drive data-informed product and business decisions across a portfolio of platforms that make our products personal, trustworthy, well-crafted, communicative, and usable by anyone, anywhere. You will play a critical role as the first dedicated analytics leader for this organization, inheriting a small, senior Data Science team and building the function around it. You will also lead Data Science for our AI-powered Product Marketing initiative. You will be a strategic partner to product and engineering leadership — shaping the questions worth asking, delivering rigorous analyses, and using data to drive change in products, strategies, and organizations.

Requirements

10+ years of work experience managing analytics teams, working collaboratively with Product and Engineering teams, and guiding data-influenced product and business planning, prioritization, and strategy development
Deep expertise in causal measurement, experimentation design, holdouts, incrementality, and topline attribution at scale
Demonstrated experience in hiring, retaining, and scaling diverse, high-performing teams
Proven experience influencing strategy and driving change across org boundaries through clear and compelling communication of data-driven insights and analyses
Strong executive communication skills with experience presenting to VP/exec-level leadership
Experience evaluating AI/ML system quality — reasoning quality, task completion, and user trust metrics

Nice To Haves

Experience leading analytics across multiple, very different problem spaces (e.g., growth, social good, design, communications, globalization)
Experience driving analytics for rapidly scaling or AI-native product lines
Track record as a hands-on technical leader who sets the bar for analytical rigor and can still do the hardest analysis themselves
Experience with both product analytics and business analytics applications
Heavy user of AI tools with a mindset toward AI-native analytics workflows
Previous experience building a data science function from a small, senior team to a scaled organization

Responsibilities

Define the Data Science operating model across a portfolio of platforms — deciding what the team should look like at each stage of scale and where to invest across diverse problem spaces including growth/personalization, social good, design craft, communications, and globalization.
Partner with leadership teams across product, engineering, and go-to-market organizations to build and strengthen a data-inspired culture, bringing innovative data insights into the key decisions for product success.
Inspire, lead, and grow a globally distributed team of data scientists, setting the hiring bar, standards, and culture for analytical rigor.
Own measurement and experimentation strategy at scale — holdouts, incrementality, and topline attribution across platforms driving tens of millions of incremental users.
Lead the measurement and evaluation flywheel for AI-powered marketing initiatives, including quality rubrics, golden-set evals, governance, and revenue tie-out.
Apply your expertise directly and through coaching the team to shape growth strategy, product optimization, design quality evaluation, communications optimization, and AI-driven automation tradeoffs.
Build strong cross-functional relationships with product and engineering leadership that make Data Science a co-pilot, not an afterthought — presenting regularly to senior leadership with crisp, actionable, defensible insights.
Drive the evaluation and quality mindset for AI systems — measuring whether AI/ML systems are delivering on reasoning quality, task completion, and user trust.
Build organizational processes and structure for scale including recruiting, new hire onboarding, team operating rhythm, and people programs.
Lead analytics through change as platforms are rebuilt to be AI-native, setting the example for AI-native analytics practices.