✦ Luna Orbit — Data & Analytics

Principal Associate, Data Scientist - Anti-Money Laundering Modeling and Advanced Data Insights

at Capital One Financial

📍 3 Locations Unknown 💰 $147K – $167K USD / year Posted April 01, 2026
Salary $147K – $167K USD / year
Type Full-Time
Experience mid
Exp. Years 3+ years
Education Not specified
Category Data & Analytics

This role involves developing machine learning models and data insights within Capital One's AML team, leveraging open-source tools and cloud platforms to detect fraud and money laundering activities.

  • Partner with cross-functional teams
  • Develop machine learning models
  • Analyze large datasets
  • Deploy models into production
  • Generate data insights

The candidate will work with Python, AWS, Spark, H2O, and Snowflake to build and deploy predictive models and perform advanced data analysis.

The ideal candidate is a data scientist with 3+ years of experience in Python, AWS, and machine learning, capable of developing predictive models and analyzing large datasets to generate actionable insights.

Experience with PythonExperience with AWSExperience with machine learning modelsExperience with statistical techniques
Experience with SparkExperience with SnowflakeExperience with text analyticsExperience deploying models
AWSH2OSparkSnowflake
PythonAWSH2OSparkMachine LearningStatistical ModelingData AnalyticsData ScienceText AnalyticsRelational Databases
PythonCondaAWSH2OSparkMachine LearningStatistical ModelingData AnalyticsData ScienceText AnalyticsRelational Databases
CreativityInnovationProblem-solvingCommunicationCollaboration
Industry Financial Services
Job Function Build and deploy machine learning models to enhance anti-money laundering efforts.
Role Subtype Data Scientist
Tech Domains Python, Amazon Web Services, Data & Analytics
Data ScientistMachine LearningPythonAWSSparkH2OData AnalyticsStatistical ModelingData ScienceText AnalyticsRelational DatabasesModel DeploymentData InsightsPredictive ModelingBig Datapythonawsmachine learningsparkh2odata sciencestatistical modelingtext analyticsrelational databasesmodel deployment

Lack of experience with Python or AWS, No machine learning experience, No statistical modeling background, No experience with model deployment

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