Senior Data Science Lead, Model Risk

Capital One; Richmond (VA); In loco; USD 209.000 - 239.000; Tempo pieno

Descrizione del lavoro

Capital One is seeking a Data Scientist to join the Model Risk Office in Richmond, VA. You will partner with data scientists, software engineers, and product managers to deliver customer-focused data products and build machine learning models across design, training, evaluation, and deployment stages.

You will leverage Python, Conda, AWS, H2O, and Spark to extract insights from billions of records, communicating complex findings to drive business decisions and risk management improvements.

Competenze

• Bachelor’s degree in a quantitative field plus 7 years of data analytics experience
• Master’s degree in a quantitative field or MBA with quantitative concentration plus 5 years of data analytics experience
• PhD in a quantitative field plus 2 years of data analytics experience
• At least 2 years of experience leveraging open source programming languages for large scale data analysis
• At least 2 years of experience with machine learning
• At least 2 years of experience utilizing relational databases

Mansioni

• 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, and more — to reveal insights
• 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

Conoscenze

Python

SQL (Relational databases)

Machine learning

Data analytics

Formazione

Bachelor's degree in quantitative field

Master's degree in quantitative field or MBA with quantitative concentration

PhD in quantitative field

Strumenti

AWS

H2O

Spark

Conda

Descrizione del lavoro

Capital One is seeking a Data Scientist to join the Model Risk Office in Richmond, VA. You will partner with data scientists, software engineers, and product managers to deliver customer-focused data products and build machine learning models across design, training, evaluation, and deployment stages.

You will leverage Python, Conda, AWS, H2O, and Spark to extract insights from billions of records, communicating complex findings to drive business decisions and risk management improvements.