Data Scientist at Concora Credit Inc.
Beaverton, OR
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Jul 1, 2026
Beaverton, OR
Jul 21, 2026
What this job asks for AI summary
A data science role focused on building and deploying machine learning models for credit risk, fraud detection, marketing, and account management within a consumer lending business. Day-to-day work spans the full model lifecycle — from sourcing and evaluating new data to training, monitoring, and documenting production models — using Python, R, SQL, and the Databricks platform. The role also involves mentoring junior analysts and contributing to a long-term enterprise modeling roadmap.
Mid level · 2+ years · National · Master's required · Full-time
“or” means any one of them counts — you don't need all of them.
Posted 2 times — it's one opening, so apply once.
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
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).
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 (7)
The JD accepts either an M.S. with 2–4 years of experience OR a Ph.D. with 1–3 years; the minimum degree is therefore a Master's, and the overall years minimum is set to 2 (the lower bound of the M.S. path).
Python and R are listed together as required tools ('Strong Programming skills in Python and/or R'), with Python explicitly preferred; they are treated as interchangeable hard gates rather than two separate requirements.
Databricks, Spark SQL, and XGBoost appear in the requirements section but are explicitly qualified as 'a plus', so they are treated as preferred rather than hard gates.
Predictive modeling experience and finance/lending domain experience are described as 'preferred', so they are marked accordingly.
No work location or metro area is specified in the posting; the CBSA fields are left blank. The mention of 'onsite fitness equipment at both locations' suggests an in-office or hybrid role, so remote is set to false.
The alternative occupation code (15-1243) reflects the model infrastructure/pipeline-building responsibilities ('design, develop, and deploy infrastructure for training, testing, and serving of models at scale'), though the primary day-to-day work is clearly data science/ML modeling.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): predictive modeling.
Read the full posting
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