Manager, Data Scientist - Financial Services

Capital One Financial

Hybrid

Quick summary

Work type: Hybrid
Location: Plano, TX
Salary: $179,400–$204,700 / yr
Posted: 22 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $175k

This role $192k

$121k most similar roles pay here $231k

This role pays more than 60% of similar roles. Most pay $135,000–$214,500 — the shaded band above. At the midpoint, this role pays about $192k versus about $175k for comparable roles.

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 498 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 495 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Manager, Data Scientist - Financial Services

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As a Data Scientist at Capital One's Auto Finance business, you will join a high-performing team focused on leveraging cutting-edge computing and machine learning technologies to analyze billions of customer records. Your daily responsibilities include developing predictive models for applications such as customer lifetime valuation, product recommendation, fraud detection, and productivity improvement through Generative AI. Ideal candidates are data experts comfortable with big data challenges, passionate about emerging technologies like open-source languages, and skilled in statistical modeling and validation. The role requires a deep understanding of financial services and the ability to drive impactful business solutions that enhance customer experiences by saving them money and time.

Skills

Python R SQL Spark Hadoop TensorFlow Scikit-learn Kafka Docker AWS Azure CI/CD Git Jupyter PostgreSQL MLOps

What you'll do

Develop advanced machine learning models to enhance customer lifetime valuation.
Implement fraud detection systems using cutting-edge technologies and big data.
Create product recommendation engines to improve customer financial experiences.
Continuously research and integrate new AI techniques into existing frameworks.
Validate and back-test statistical models to ensure accuracy and reliability.

What we're looking for

Extensive experience with big data and machine learning technologies.
Proven ability to build, validate, and back-test statistical models.
Strong background in customer lifetime valuation and product recommendation systems.
Experience in fraud detection and productivity improvement using AI.
Proficiency in open-source languages and a commitment to technical innovation.

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