Principal Associate, Data Scientist - Bank Operations Data Science

Capital One Financial

Quick summary

Work type: On-site
Location: McLean, VA
Salary: $161,800–$184,600 / yr
Posted: 3 days ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $175k

This role $173k

$126k most similar roles pay here $228k

This role pays more than 61% of similar roles. Most pay $141,550–$208,989 — the shaded band above. At the midpoint, this role pays about $173k 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 814 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 809 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Principal Associate, Data Scientist - Bank Operations Data Science

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As a Principal Associate in the Bank Operations Data Science team, you will work on developing advanced machine learning models to enhance internal capabilities such as document reading, anomaly detection, and operational forecasting. Your daily tasks include leveraging Python, Snowflake, and other technologies to extract insights from large datasets, collaborating closely with call center operations to automate processes and improve customer service through summarization tools. Ideal candidates are innovative, creative, technically proficient, and statistically minded, with a preference for those who can identify and mitigate risks associated with LLMs and maintain technical documentation effectively. This role involves working on cutting-edge technologies at scale to solve complex business problems in the financial services industry.

Skills

Python Snowflake LLMs Neural Networks Transformer Architectures Natural Language Processing CI/CD SQL Data Visualization Scikit-learn Pandas NumPy TensorFlow PyTorch AWS Azure Google Cloud Platform PostgreSQL MLOps

What you'll do

Develop machine learning models using Python and Snowflake to analyze large datasets.
Streamline call center operations by automating and summarizing calls.
Identify and mitigate risks associated with LLMs in operational contexts.
Create and maintain technical documentation for data science projects.
Implement neural networks, transformer architectures, and other emerging technologies.
Collaborate on anomaly identification and natural language processing tasks.

What we're looking for

Extensive experience in machine learning models using neural networks and LLMs.
Strong background in Python and data processing technologies like Snowflake.
Ability to work with large volumes of numeric and textual data effectively.
Proven skills in call center operations optimization, including summarization and automation.
Experience in identifying and mitigating risks associated with LLMs.
Capable of creating and maintaining detailed technical documentation.

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