Data Scientist – Fraud Authentication

Data Scientist – Fraud Authentication

Capital One – [Onsite]

Location - Virginia
Role Type: Contract
Experience: 5+ Years

About the Role

Capital One is seeking a talented Data Scientist to join the US Card Fraud Authentication Data Science team. This team works at the intersection of fraud prevention and customer experience, using advanced analytics and machine learning to identify evolving fraud patterns and develop scalable solutions.

You’ll work with technologies including Python, AWS, Spark, H2O, and SQL while partnering with data scientists, software engineers, product managers, and business stakeholders.

Key Responsibilities

• Analyze complex and ambiguous fraud problems to identify opportunities for machine learning.
• Design, develop, evaluate, validate, and implement machine learning models.
• Leverage Spark and AWS to analyze large-scale datasets and identify fraud patterns.
• Develop scalable data science solutions that improve fraud prevention and customer experience.
• Collaborate with cross-functional teams to translate business problems into technical solutions.
• Communicate complex analytical and technical concepts clearly to business stakeholders.
• Apply statistical techniques and model evaluation methods, including confusion matrices and ROC curves.
• Work with classification, clustering, time series, sentiment analysis, and deep learning techniques.

Required Qualifications

• Bachelor’s Degree in Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field plus 5 years of data analytics experience.
• OR Master’s Degree / quantitative MBA plus 3 years of data analytics experience.
• OR PhD in a quantitative field.
• Strong experience in Python, SQL, Machine Learning, and statistical modeling.
• Experience building, validating, and backtesting machine learning models.
• Experience working with cloud computing platforms and open-source technologies.

Preferred Qualifications

• 3+ years of experience with Python, Scala, or R.
• 3+ years of Machine Learning experience.
• 3+ years of SQL experience.
• 1+ year of AWS experience.
• Experience with Spark, H2O, and large-scale data processing.
• Experience in fraud detection, risk analytics, banking, or financial services is a plus.

Top Skills

Primary Skills: Python SQL Machine Learning Spark AWS
Secondary Skills: H2O Statistics Fraud Analytics Model Validation