Principal Associate, Data Scientist - People Strategy & Analytics

Capital One National Association; McLean (VA); On-site; USD 161,800 - 184,600; Full time

Benefits offered by this job

Performance-based incentives

Health and wellness benefits

Remote working options

Job summary

Capital One National Association is seeking a Principal Associate, Data Scientist to apply AI and machine learning in People Strategy & Analytics. This role involves building models to enhance HR efficiency and decision-making using large data sets.

The ideal candidate will have a quantitative background with at least 3-5 years of experience in data analytics, including expertise in Python, SQL, and AWS. A competitive salary range of $161,800 – $184,600 is offered, along with performance-based incentives.

Qualifications

• Strong background in data analytics using open-source tools.
• Experience with AI/ML tools and cloud platforms.
• Ability to build and validate complex models.

Responsibilities

• Develop and implement machine learning models for HR applications.
• Collaborate across teams to leverage data for business outcomes.
• Utilize a broad technology stack for data insights.

Skills

Natural language processing

Machine learning

Python

SQL

Statistical modeling

Education

Bachelor's Degree in a quantitative field with 5 years experience

Master's Degree in a quantitative field with 3 years experience

PhD in a quantitative field

Tools

AWS

Hugging Face

PyTorch/TensorFlow

Snowflake

Job description

Principal Associate, Data Scientist - People Strategy & Analytics

Data is at the center of everything we do. As a startup, we disrupted the credit card industry with personalized offers using statistical modeling and relational databases. Fast forward, and this innovation has made us a Fortune 200 company and a leader in data‑driven decision making.

People Strategy & Analytics brings data, analytics, and insights to shape critical talent decisions and strategy. The team works closely with HR partners and senior executives to shape talent policy, automate real‑time data, and improve decision‑making.

Role Description

As a Data Scientist on this team, you’ll be at the leading edge of applying analytics to talent, combining AI, machine learning, and social science to build models that understand associate behavior, improve HR efficiency, and inform strategies.

In this role, you will:

• Build natural language processing and machine learning models through all phases of development, from design through training, evaluation, validation, and implementation.
• Apply expertise in using open‑source large language models (LLMs) through prompt engineering, retrieval‑augmented generation (RAG), and evaluation metric frameworks for business‑specific applications.
• Partner with a cross‑functional team of data scientists, software engineers, business analysts, and product managers to deliver industry‑leading HR tools and AI‑powered products.
• Leverage a broad stack of technologies—Python, SQL, AWS, LangChain, Hugging Face Transformers, VectorDBs, PyTorch/TensorFlow, and more—to reveal insights hidden within large volumes of numeric and textual data.
• Collaborate with internal stakeholders, translating complex data science work into tangible, aligned business outcomes.

The Ideal Candidate is:

• Passionate about human capital and excited by the value you can add to the company and its associates.
• Innovative, continually researching and evaluating emerging technologies and applications.
• Creative, adept at bringing definition to big, undefined problems and asking hard questions.
• Technical, comfortable with open‑source languages and passionate about developing data science solutions using open‑source tools and cloud platforms.
• Statistically minded, with experience building, validating, and backtesting models; comfortable interpreting a confusion matrix or ROC curve; and familiar with clustering, classification, sentiment analysis, time series, and deep learning.

Basic Qualifications

• Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
  • A Bachelor’s Degree in a quantitative field plus 5 years of experience performing data analytics.
  • A Master’s Degree in a quantitative field plus 3 years of experience performing data analytics.
  • A PhD in a quantitative field.

Preferred Qualifications

• Master’s Degree in STEM plus 3 years of experience in data analytics, or PhD in STEM.
• At least 1 year of experience working with AWS.
• At least 3 years’ experience in Python.
• At least 3 years’ experience with machine learning.
• At least 3 years’ experience with SQL.
• At least 2 years’ experience with relational databases such as Snowflake.
• At least 2 years’ experience with AI/ML tools and ecosystems such as Hugging Face, VectorDBs, or PyTorch/TensorFlow.

Capital One will consider sponsoring a qualified applicant for employment authorization for this position.

Salary for this role is $161,800 – $184,600 for Principal Associate, Data Science in McLean, VA. Compensation may include performance‑based incentives such as cash bonuses and long‑term incentives.

Capital One is an equal‑opportunity employer (EOE, including disability/veteran) committed to non‑discrimination in accordance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace.