Senior Data Scientist, Credit
Mission Lane
$120,000–$135,000from the description
Jul 20, 2026
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Jul 21, 2026
What this job asks for AI summary
This role centers on building, deploying, and maintaining machine learning models that drive credit and lending decisions at a consumer fintech company. The work involves collaborating with business and technical stakeholders to develop new data sources, refine modeling approaches, and apply sound risk management practices. It suits a generalist data scientist with production ML experience and solid software engineering habits.
Mid level · 3+ years · Remote · Full-time
Advertised as Senior, but the requirements read as Mid.
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 28,000 people nationally plausibly meet what this posting asks for (data scientists). range 11,800–42,000
Applicant volume Heavy — This req sits in a large pool with little in its requirements to thin it, and auto-apply tools fire at everything in the occupation. Applying early and leading with the rare skills below is what gets read.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $122,874 (middle half $87,544–$162,374). 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 28, 2026. It is a model, not a headcount.
Why we read it this way (5)
The posting offers two equivalent experience paths: PhD in a quantitative field + 1+ years, OR BS/MS + 3+ years. The overall years minimum is set to 3 (the lower bound of the non-PhD path, which is the more common route). No specific degree is hard-required because equivalent experience is accepted across both tracks.
The PyData stack (numpy, scikit-learn, pandas) and production supervised learning experience are stated in the 'You are a person who' requirements block and are treated as hard gates.
Spark, Kubernetes, Airflow, MLflow, Chalk, BentoML, DVC, and neural networks appear in an 'interested in' or 'bonus points' framing and are marked preferred.
Seniority is assessed as Mid despite the 'Senior' title: the experience floor (1–3 years depending on degree) and the collaborative/generalist framing align more closely with a mid-level role than a true senior scope. The advertised title is preserved as Senior.
Caller marked this a fully-remote role — scored against the national candidate pool.
Read the full posting
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