Senior Data Scientist - Growth
Mercury is hiring a Senior Data Scientist - Growth for a remote role open to applicants in United States. It pays $201k-$251k a year and Level rates it ; you can apply on Mercury.
Level's read on this job
- On Level's scale, this data scientist role is Little AI ●○○○: aI is not part of the work.
- Pay on this posting starts 21% higher than the typical data scientist posting on Level.
- This is listed as a remote role.
- The posting mentions Python, SQL and A B Testing among its tools and skills.
- Mercury has 72 other open roles on Level.
AI in this role
Partner with growth and product leaders to analyze metrics, build driver trees, and run experiments to drive customer acquisition.
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 similar; familiarity with Snowflake and dbt is a plus.
- Be comfortable with ambiguity and with respectfully disagreeing with senior stakeholders, backed by evidence.
- Be a clear, concise communicator who leads with the point and tailors the message to technical and non-technical audiences.
- Nice to have: experience in consumer or SMB fintech, or with mobile product analytics.
* Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.
Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.
#LI-RA1
Total Rewards
The total rewards package at Mercury includes base salary, equity (stock options/RSUs), and benefits.
Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.
Our target new hire base salary ranges for this role are the following:
US employees (any location):$200,700—$250,900 USDCanadian employees (any location):$189,700—$237,100 CADHow we rate this
Senior Data Scientist - Growth at Mercury rates 20 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data scientist jobs at this level
Pay
- This job starts at
- $201k
- Typical data scientist job
- $166k
This posting starts 21% above the typical data scientist job. See data scientist jobs
Questions you could be asked
- Tell me about a project where growth analytics was part of your work. What did you do?
- Tell me about a project where product analytics was part of your work. What did you do?
- Tell me about a project where experimentation was part of your work. What did you do?
- Tell me about a project where data science was part of your work. What did you do?
- Walk me through how you've used Python in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Growth Analytics, Product Analytics, Experimentation, Data Science, and Python. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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