✦ Luna Orbit — Data & Analytics

Manager, Data Scientist

at Capital One Financial

📍 2 Locations Unknown 💰 $197K – $225K USD / year Posted March 27, 2026
Salary $197K – $225K USD / year
Type Full-Time
Experience mid
Exp. Years 3+ years
Education Not specified
Category Data & Analytics

This role involves leveraging data science and machine learning techniques to analyze customer data, build models, and support risk management initiatives within a financial services environment.

  • Partner with cross-functional teams
  • Build and validate models
  • Use cloud platforms
  • Analyze large datasets
  • Contribute to risk decision-making

The technical environment includes Python, AWS, Spark, statistical modeling, and data analysis tools, focusing on scalable machine learning solutions and data governance.

The ideal candidate is a mid-level data scientist with hands-on experience in machine learning, statistical modeling, and cloud platforms like AWS. They are innovative, collaborative, and capable of analyzing large datasets to inform business decisions.

Hands-on experience with data science solutionsExperience with cloud computing platformsModel development and validationKnowledge of statistical methods
Open-source toolsTextual data analysisBig data technologiesModel deploymentRisk management
PythonCondaAWSSpark
PythonCondaAWSSparkMachine LearningStatistical ModelingData AnalysisModel ValidationData Governance
PythonCondaAWSSparkMachine LearningStatistical ModelingData AnalysisModel ValidationData Governance
InnovationCreativityCommunicationProblem-solvingCollaboration
Industry Financial Services / Fintech
Job Function Data science and machine learning model development and validation
Role Subtype Data Scientist
Tech Domains Python, AWS, Apache Spark, Data Analysis, Machine Learning
data scientistmachine learningpythoncongaawssparkstatistical modelingdata analysismodel validationdata governancecloud computingbig datarisk managementtext analysismodel deploymentcloud platforms

No experience with data science solutions, Lack of cloud computing experience, No background in statistical modeling, No experience with model validation

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