Mercury
Tech / AI / Software
SeniorDataScienceManager
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Science Manager at Mercury. Skills: data science, experimentation, attribution, causal inference, growth, monetization, product analytics, revenue forecasting, capital allocation. Lead and develop a team of Data Scientists embedded across go-to-market, growth product, monetization, and core product experiences. Define the measurement and experimentation strategy across the customer lifecycle — from acquisition and activation to monetization, expansion, and retention — ensuring our in”
What You'll Achieve.
drive long-term value; define how we measure performance; prioritize investments; accelerate value creation across the customer lifecycle; ensure our most important decisions are grounded in trusted data and clear experimentation frameworks; shape roadmaps; evaluate ROI; guide revenue forecasting and capital allocation decisions; influence product direction and revenue strategy; increase team leverage; power reliable, AI-enabled insights; balance user value, growth, and long-term business impact; drive revenue outcomes
Industry & Context.
Translate complex quantitative signals into clear insights
What They're Looking For.
Must Have
10+ years of experience, 3+ years leading high-performing data teams, deep experience in growth, monetization, and product analytics, proven track record of partnering with Product, Marketing, Sales, and Finance to shape roadmaps and drive revenue outcomes, business judgment, ability to balance analytical rigor with decision velocity in high-impact commercial environments, highly fluent in experimentation design, attribution, and causal inference, ability to raise the bar on analytical craft across a team of senior ICs, experience building scalable analytics frameworks and self-serve capabilities that increase leverage and support AI-enabled insight generation within growth and product domains, ability to set clear priorities that balance user value, growth, and long-term business impact
Nice to Have
PhD preferred, specific ML framework experience, cloud platform certs
What You'll Do.
Lead and develop a team of Data Scientists embedded across go-to-market
and core product experiences
Define the measurement and experimentation strategy across the customer lifecycle — from acquisition and activation to monetization
and retention — ensuring our investments are grounded in rigorous analysis and trusted data
Elevate the craft of experimentation
pricing and monetization analytics
and commercial performance measurement
balancing analytical precision with decision velocity
Partner closely with Product
and Finance to shape roadmaps
and guide revenue forecasting and capital allocation decisions
Translate complex quantitative signals into clear insights that influence product direction and revenue strategy
Increase team leverage by building scalable analytics systems and self-serve capabilities that power reliable
AI-enabled insights across growth
and core product experiences
Operate effectively in ambiguity
setting clear priorities that balance user value
and long-term business impact
How You'll Work.
Team & Collaboration
Partner closely with Product, Engineering, Marketing, Sales, and Finance to ensure our most important decisions are grounded in trusted data and clear experimentation frameworks; Partner closely with Product, Marketing, Sales, and Finance to shape roadmaps, evaluate ROI, and guide revenue forecasting and capital allocation decisions
Communication Scope
Translate complex quantitative signals into clear insights
Process & Methodology
setting clear priorities
Full Job Description
In 1923, Claude Hopkins published Scientific Advertising, introducing early ideas around experimentation, attribution, and measurable decision-making. Behind the book was a team that meticulously designed, executed, and measured campaigns — setting the foundation for modern, data-driven growth. At Mercury, that mindset extends beyond marketing. It spans how we acquire customers, how we activate and convert them, and how we design product experiences that drive long-term value. We’re looking for a Senior Data Science Manager to lead the data science powering Mercury’s revenue and product value engine. This team supports Go-To-Market functions across Finance, Marketing, and Sales, drives growth product experimentation across activation and conversion, and partners on core product experiences like Spend, Expense Management, and Invoicing. In this role, you’ll define how we measure performance, prioritize investments, and accelerate value creation across the customer lifecycle — with a high bar for rigor and a bias toward execution. You’ll partner closely with Product, Engineering, Marketing, Sales, and Finance to ensure our most important decisions are grounded in trusted data and clear experimentation frameworks. Here are some things you’ll do on the job: Lead and develop a team of Data Scientists embedded across go-to-market, growth product, monetization, and core product experiences Define the measurement and experimentation strategy across the customer lifecycle — from acquisition and activation to monetization, expansion, and retention — ensuring our investments are grounded in rigorous analysis and trusted data Elevate the craft of experimentation, pricing and monetization analytics, and commercial performance measurement, balancing analytical precision with decision velocity Partner closely with Product, Marketing, Sales, and Finance to shape roadmaps, evaluate ROI, and guide revenue forecasting and capital allocation decisions Translate complex quantitative sig
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