Mercury

Tech / AI / Software

SeniorDataScienceManager

$239–299k Any Office or Remote Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“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.

Tech / AI / Software
Problems you'll solve

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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