Senior Data Scientist Fraud ML & Risk Analytics

Capital One; McLean (VA); On-site; USD 162,000 - 185,000; Full time

Job summary

Capital One is seeking a Principal Associate, Data Scientist for the SBB Fraud team in McLean, VA. You will partner with cross-functional teams to deploy fraud models at scale, leveraging Python, Spark, AWS, and related tools to extract insights from billions of records.

You will build models end-to-end, from design to deployment, translating complex analyses into actionable business outcomes. The Ideal Candidate has strong statistical modeling, data analytics, and machine learning experience

Qualifications

• Bachelor's degree in a quantitative field plus 5 years of analytics experience.
• Master's degree in a quantitative field or MBA with a quantitative concentration plus 3 years of analytics.
• A PhD in a quantitative field.
• Master’s Degree in STEM plus 3 years of analytics or PhD in STEM.

Responsibilities

• Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love.
• Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark — to reveal insights from huge volumes of data.
• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation.
• Translate the complexity of your work into tangible business goals.

Skills

Statistical modeling

Data analytics

Communication

Cross-functional collaboration

Education

Bachelor's degree in quantitative field

Master's degree in quantitative field

PhD in quantitative field

MBA with quantitative concentration

Tools

Python

SQL

Spark

AWS

H2O

Conda

Dask

Job description

Capital One is seeking a Principal Associate, Data Scientist for the SBB Fraud team in McLean, VA. You will partner with cross-functional teams to deploy fraud models at scale, leveraging Python, Spark, AWS, and related tools to extract insights from billions of records.

You will build models end-to-end, from design to deployment, translating complex analyses into actionable business outcomes. The Ideal Candidate has strong statistical modeling, data analytics, and machine learning experience