Applied Data Scientist

Capital One Financial

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Cambridge, MA
Salary
$116,600–$133,100 / yr
Employment
Part-time
Posted
3 days ago
Freshness
Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $170k
This role $125k
$103k most similar roles pay here $226k

This role pays less than 88% of similar roles. Most pay $126,800–$214,000 — the shaded band above. At the midpoint, this role pays about $125k versus about $170k 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 1043 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1037 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Applied Data Scientist

As a Part-Time Applied Data Scientist, you will join a high-performing team focused on analytical, risk management, machine learning, deep learning, and GenAI initiatives. You will support core data teams by performing essential tasks such as querying, cleaning, and preprocessing large structured and unstructured datasets to ensure quality for downstream analysis. Your daily responsibilities include feature engineering from raw bureau records and transactional data streams, executing and monitoring machine learning workflows, and conducting qualitative and quantitative investigations to identify trends or risks. You will also aggregate findings to inform credit policy and pilot programs. To succeed, you must utilize Python, GenAI tools like Claude Code, Codex, and Gemini AI Suite, and work with large-scale relational or unstructured databases. This role addresses financial services challenges by turning data into insights regarding behavior, intent, and sentiment.

What you'll do

  • Query, clean, and preprocess large structured and unstructured datasets to ensure data quality for analysis.
  • Write, test, and validate code to extract analytical features from raw bureau records and transactional data.
  • Run and monitor machine learning workflows to generate model diagnostics and track system performance.
  • Aggregate findings from internal and external sources to inform credit policy and pilot programs.
  • Perform qualitative and quantitative investigations to identify trends, anomalies, and potential data risks.
  • Support the tactical data, analytical, and modeling needs of a cross-functional team.

What we're looking for

  • Must be currently pursuing a Bachelor’s degree in a quantitative field such as mathematics, science, statistics, or engineering.
  • Must be a current student at Massachusetts Institute of Technology.
  • Must be located in the continental United States.
  • At least 6 months of experience or academic work using open source programming languages.
  • At least 6 months of experience or academic work using machine learning and AI applications.
  • 1+ year experience or academic work in statistics, mathematics, computer science, machine learning, GenAI, and data science.
  • 1+ year experience or academic work with large scale relational or unstructured databases.
  • 1+ year experience with Python and GenAI tools (preferred); students with scholarships, honors, or departmental distinctions (preferred).

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