Alpharetta, GA

Salary
Posted
Jul 22, 2026
Location
Alpharetta, GA
Last confirmed open
Jul 23, 2026

What this job asks for AI summary

A senior individual-contributor role focused on building and maintaining machine learning models that support merchant analysis, offer recommendations, and digital onboarding personalization within a fintech payments company. Day-to-day work spans model development across segmentation, propensity, ranking, and recommendation tasks, plus experiment design, production handoffs with ML engineers, and communicating results to non-technical stakeholders. Suits an experienced data scientist comfortable working across cloud ML platforms and cross-functional teams.

Senior level · 8+ years · Full-time

Must have (7)
PythonSQLpandasscikit-learnAWS SageMaker, Azure Ml or Vertex AiSnowflakeAWS S3
Nice to have (3)
MLOpsfeature storesLLMs

“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

What gives you an edge
AWS SageMaker5%

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

What won't set you apart
Python88%SQL72%pandas72%scikit-learn58%

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 (5)

No specific work location city is stated in the posting, only a list of states where the role CANNOT be performed (Colorado, California, DC, Hawaii, Illinois, Massachusetts, Maryland, Minnesota, New Jersey, New York, Nevada, Rhode Island, Vermont, Virginia, Maine, Washington). CBSA/metro could not be determined.

The cloud platforms requirement uses 'such as' framing ('AWS SageMaker, Snowflake, S3, Glue, or comparable platforms'), indicating the specific tools are illustrative of a required capability rather than hard gates on each individual product. They are captured as required per the substitution-qualifier rule, with well-known alternatives noted for SageMaker.

The degree requirement states 'Bachelor's degree … or equivalent industry experience,' so no formal degree is hard-gated.

MLOps, feature stores, LLMs, and Generative AI appear exclusively under the 'Experience That Would Be Great to Have' section and are marked preferred accordingly.

The posting explicitly states this is a full-time, direct-hire position and is on-site Monday through Friday.

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