Charlotte, NC

Salary
$118,000–$149,000from the description
Posted
Jul 22, 2026
Location
Charlotte, NC
Last confirmed open
Jul 23, 2026

What this job asks for AI summary

A senior individual-contributor data science role focused on fraud prevention at a financial services firm. Day-to-day work spans analyzing large fraud datasets, building and monitoring machine learning models, evaluating rule-based detection systems, and prototyping agentic and generative AI solutions within an AWS environment. The role bridges fraud operations and technology teams, requiring both deep quantitative skills and the ability to communicate findings to non-technical stakeholders.

Senior level · 5+ years · New York-Newark-Jersey City, NY-NJ-PA · Full-time

Must have (6)
Python or RSQLmachine learningstatistical modelingclassification modelsanomaly detection
Nice to have (5)
AWSAWS AgentCoreAmazon QKiroLLMs

“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 170 people in the New York-Newark-Jersey City, NY-NJ-PA area plausibly meet what this posting asks for (data scientists). range 90–230

Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.

What gives you an edge
anomaly detection5%

Rare in this occupation — lead with these, and say what you built with them.

What won't set you apart
Python88%machine learning80%SQL72%statistical modeling60%

Most people in this occupation already list these. Still required — just not what gets you shortlisted.

What the occupation pays Median $138,970 (middle half $103,548–$176,968). 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 (11)

The job title is 'Lead Data Scientist' and the role is classified at Career Level 8IC, which TIAA typically uses for senior individual contributors; the scope (owning models end-to-end, cross-team stakeholder management, strategic recommendations) supports a Senior band rather than Staff or Principal.

The degree requirement states 'University (Degree) Preferred' — not required — so the degree requirement is set to None.

Work experience is stated as '5+ Years Required; 7+ Years Preferred'; the overall years minimum reflects the hard floor of 5.

Python and R are presented as interchangeable alternatives ('Python or R') in the Required Skills section; Python is listed as the primary name with R as the alternative.

Classification, regression, clustering, and anomaly detection are all listed as required ML techniques; they are captured as separate required skills rather than collapsed into a single generic 'ML' entry.

AWS AgentCore, Amazon Q, and Kiro appear under both the duties narrative and the Preferred Skills section; they are marked preferred because the Preferred Skills section explicitly frames them as 'a plus' or 'a strong advantage.'

Generative/agentic AI (LLMs) is captured as preferred because the JD frames it as a prototype/contribution activity and lists AWS AgentCore exposure as a preferred advantage rather than a hard gate.

Model Risk Management frameworks appear only under Preferred Skills ('is a plus') and are marked accordingly.

The posting does not specify a city; TIAA's headquarters is in New York, NY, and the posting references an in-office collaborative environment — CBSA set to New York-Newark-Jersey City. Hiring managers should confirm the actual office location.

The 'Related Skills' section (Business Acumen, Data Preprocessing, Data Science, Innovation, etc.) lists generic concepts and soft skills rather than named technologies, so those entries are omitted per extraction rules.

Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): Model Risk Management.

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