Data Scientist, Fraud Prevention & Authentication

Software Technology Inc.; Virginia (MN); On-site; USD 120,000 - 170,000; Full time

Job summary

Capital One is seeking a Data Scientist to join the US Card Fraud Authentication Data Science team. You will leverage Python, AWS, Spark, H2O, and SQL to build ML models and improve authentication decisions across billions of records.

You will partner with business stakeholders, data scientists, software engineers, and product managers to design, validate, and implement scalable fraud-prevention solutions that balance customer experience and security.

Qualifications

• Bachelor's degree in a quantitative field with 5+ years of data analytics experience.
• Master's degree in a quantitative field or MBA with quantitative concentration plus 3+ years of data analytics experience.
• PhD in a quantitative field (Statistics, Economics, OR, Analytics, Mathematics, CS).

Responsibilities

• Dive into ambiguous fraud landscapes to identify ML opportunities and prototype solutions.
• Harness big data ecosystems (Spark, AWS) to uncover patterns for fraud-prevention strategies.
• Partner with cross-functional teams to deliver a product customers love.
• Build ML models through design, training, evaluation, validation, and implementation.
• Bridge technical complexity and business strategy, articulating the why behind solutions.

Skills

Python

AWS

Spark

H2O

SQL

Education

Bachelor's Degree in a quantitative field

Master's Degree in a quantitative field or MBA with quantitative concentration

PhD in a quantitative field

Job description

Capital One is seeking a Data Scientist to join the US Card Fraud Authentication Data Science team. You will leverage Python, AWS, Spark, H2O, and SQL to build ML models and improve authentication decisions across billions of records.

You will partner with business stakeholders, data scientists, software engineers, and product managers to design, validate, and implement scalable fraud-prevention solutions that balance customer experience and security.