Data Scientist ll - Digital Intelligence
Socure · Carson City, NV
$140,000–$170,000
Jul 15, 2026
Carson City, NV
Jul 21, 2026
What this job asks for AI summary
A mid-level data science role on a Digital Intelligence team focused on fraud detection and identity risk. The work centers on building machine learning features and risk signals from device, network, browser, session, and behavioral telemetry at scale — including handling noisy data, imperfect labels, and adversarial patterns like spoofing and automation. The role suits someone with 5+ years of applied ML experience who can work independently on scoped projects while collaborating across engineering, product, and risk teams.
Mid level · 5+ years · Remote · Full-time
“or” means any one of them counts — you don't need all of them.
Posted 4 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
Roughly 14,200 people nationally plausibly meet what this posting asks for (data scientists). range 4,200–21,300
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).
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 (8)
The title 'Data Scientist II' maps to a Mid-level band; the 5+ years requirement and scope (independently delivering well-scoped projects, mentoring juniors, partnering cross-functionally) are consistent with Mid rather than Senior.
Degree requirement is None: the JD explicitly accepts 'equivalent practical experience' as an alternative to any formal degree.
pandas is listed alongside NumPy, scikit-learn, XGBoost, TensorFlow, and PyTorch as a single 'such as' group under requirements; pandas is used as the primary name with the others captured as alternatives since the JD treats them as interchangeable examples of the same library requirement.
Spark/PySpark/Databricks are listed as a single 'such as' group under requirements; Spark is the primary with PySpark and Databricks as alternatives.
Supervised learning, unsupervised learning, and feature engineering are named as concrete technical competencies explicitly required in the Job Requirements section, not merely soft concepts.
All preferred qualifications (fraud/identity domain background, device/browser fingerprinting, high-cardinality encoding techniques, production ML monitoring, explainability) are listed under a clearly labelled 'Preferred Qualifications' section.
No compensation figures are stated in the posting.
Caller marked this a fully-remote role — scored against the national candidate pool.
Read the full posting
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