Principal Associate Data Scientist, Global Payments Network: Data Solutions and Modeling

Capital One Financial

Confirmed live today Low trust

Quick summary

Work type: On-site
Location: Anytown, IL
Employment: Full-time
Posted: 126 days ago
Freshness: Confirmed live today

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Salary context

How this pay compares to similar roles

Similar $193k

$140k $240k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $162,037–$224,747.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 2107 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1107 roles with salary data.

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At a glance

TL;DR · Principal Associate Data Scientist, Global Payments Network: Data Solutions and Modeling

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The Principal Associate, Data Scientist - Global Payments Network: Data Solutions and Modeling joins the Data Solutions and Model team to build machine learning and AI agents. This role involves partnering with cross-functional teams of data scientists, software engineers, and product managers to deliver products for the Global Payment Network. You will build machine learning models through all phases of development, including design, training, evaluation, validation, and implementation. Key responsibilities include revealing insights within huge volumes of numeric and textual data to support fraud, risk, merchant acceptance, and monitoring. Required technologies and skills include Python, Conda, AWS, H2O, Spark, Scala, R, and SQL. Candidates should also possess experience with Large Language Models, embedding models, vector databases, and designing autonomous AI workflows.

What does a Data Scientist earn?

Median $173200 from 338 postings across 66 companies.

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Skills

Python AWS Spark H2O SQL Scala R Machine Learning Large Language Models Vector Databases Conda AI Agents Data Analytics

What you'll do

Build machine learning models through all phases of development including design, training, evaluation, validation, and implementation.
Leverage Python, Conda, AWS, H2O, and Spark to extract insights from large volumes of numeric and textual data.
Develop machine learning and AI agents to support fraud risk, merchant acceptance, and merchant intelligence.
Design and implement AI workflows and autonomous AI agents.
Utilize Large Language Models, embedding models, and vector databases to solve complex problems.
Translate complex technical work into tangible business goals for stakeholders.
Research and evaluate emerging technologies and state-of-the-art methods for application in data science.

What we're looking for

A Bachelor's Degree in a quantitative field plus 5 years of experience performing data analytics.
A Master's Degree in a quantitative field or an MBA with a quantitative concentration plus 3 years of experience performing data analytics.
A PhD in a quantitative field.
Master’s Degree in a STEM field plus 3 years of experience in data analytics, or a PhD in a STEM field (preferred).
At least 3 years of experience in Python, Scala, or R (preferred).
At least 3 years of experience with machine learning (preferred).
At least 3 years of experience with SQL (preferred).
Experience with LLMs, embedding models, vector databases, and designing AI workflows or autonomous agents (preferred).

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