Senior Data Scientist - Growth

Mercury; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Mercury is seeking a Growth Data Scientist to partner with Growth product, design, engineering and marketing to shape how we acquire, activate and retain customers across business and personal banking. You will frame the “why” behind what we build and translate data into actionable growth opportunities.

You’ll work end-to-end on growth analytics, including experiment design and communicating findings to executives, helping set direction for growth initiatives and revenue generation.

Qualifications

• 6+ years of experience in data science, product analytics or growth analytics.
• 3+ years partnering closely with product growth teams.
• Strong product sense with a track record of shaping product direction.

Responsibilities

• Partner with Growth product, design, engineering and marketing leaders to identify high-impact questions and influence what gets built.
• Own the growth funnel end to end, from first visit through signup, activation and retention, building metrics and narratives.

Skills

SQL

Python

R

Tools

Amplitude

Hex

Omni

Job description

In the 1840s, Charles Babbage and Ada Lovelace worked on an early version of the computer known as the “Analytics Engine”. In the words of computing historian Doron Swade, “What Lovelace saw...was that numbers could represent entities other than quantity” and together they laid the foundation for general-purpose computing.

While much has changed since then, the importance of numbers in building great technology remains. We’re looking for Data Scientists who can help us build our analytics engine by making meaning from data and identifying opportunities for improvement.

As a Growth Data Scientist at Mercury, you will partner with Growth product, design, engineering and marketing leaders to shape how Mercury acquires, activates and retains customers across business and personal banking*. This is a strategic, product-facing role: you’ll frame the “why” behind what we build, size opportunities, and turn the growth funnel into clear, prioritized recommendations. You will work as a full-stack Data Scientist on projects end to end and build deep domain expertise at the intersection of Data Science, Product and Growth. You will help set the direction for how Growth measures success and decides where to invest, in line with Mercury’s broader product and company goals.

Here are some things you’ll do on the job:

• Partner with Growth product, design, engineering and marketing leaders to identify the highest-impact business questions, and influence what gets built and why.
• Own the growth funnel end to end, from first visit through signup, approval, activation and retention, building the metrics, driver trees and narratives that show where we’re winning and where we’re not.
• Size opportunities and help prioritize the Growth roadmap and annual planning, making clear recommendations even when data is incomplete.
• Design, analyze and communicate experiments (A/B tests and quasi-experimental methods) that tell teams whether a change worked and what to do next.
• Right-size your work to the decision: fast and directional when that’s what’s needed, rigorous when the stakes call for it.
• Collaborate with other Data Scientists, Data Engineers and Analytics Engineers to build trusted, self-serve growth metrics.
• Communicate findings and recommendations to audiences at all levels, including executives, with a clear point of view that improves entrepreneurs’ lives and generates revenue for Mercury.

You should:

• Have 6+ years of experience in data science, product analytics or growth analytics, including 3+ years partnering closely with product growth teams.
• Have strong product sense and a track record of shaping product direction, not just measuring it, including times your work changed what a team built.
• Have deep experience with experiment design and analysis, as well as funnel, cohort and retention analysis.
• Have fluency in SQL and a statistical programming language (e.g. Python, R).
• Have experience with product analytics and BI tools such as Amplitude, Hex, Omni or simila