Senior Data Scientist, Growth Marketing at Rocket Money
San Francisco, CA
$180,000–$235,000from the description
Jul 28, 2026
San Francisco, CA
Jul 29, 2026
What this job asks for AI summary
A Senior Data Scientist role at a personal finance app, focused on marketing efficiency and product experimentation. The work centers on building customer lifetime value models, media mix attribution models, and causal inference frameworks, as well as designing and scaling a self-service experimentation platform for product and CRM teams. The role requires both hands-on modeling and cross-functional leadership to translate data science outputs into operational marketing and product decisions.
Senior level · 6+ years · San Francisco, CA · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 500 people in the San Francisco, CA area plausibly meet what this posting asks for (data scientists). range 260–650
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $173,851 (middle half $133,298–$217,653). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 29, 2026. It is a model, not a headcount.
Why we read it this way (5)
The posting requires 'at least one scripting language' without naming a specific one; Python is the dominant scripting language in data science and the most likely intended tool, listed here with common alternatives (R, Scala). Adjust if the team uses a different primary language.
The 'deep experience in several of the following' phrasing (customer segmentation, CLV modeling, A/B testing/causal inference, media mix modeling) implies not all four are individually required, but the role's described responsibilities make all four effectively central — they are marked required accordingly.
Location is inferred as San Francisco based on the reference to the San Francisco Fair Chance Ordinance; the posting does not explicitly state a city or confirm remote eligibility.
Fintech/banking/finance domain experience is listed as 'a plus' and is omitted from the skills list as it is explicitly optional.
Ignored 2 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): customer lifetime value modeling, media mix modeling.
Read the full posting
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