Data Science Lead, Model Risk Office

Capital One

Richmond (VA)

On-site

USD 205,000 - 234,000

Full time

14 days+

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Job summary

Capital One in Richmond, VA is seeking a Senior Manager, Data Science to lead the Model Risk Office and drive risk-aware data-driven decision making. You’ll partner with data scientists, engineers and product managers to identify model risks, build challenger models, and shape risk strategy at the enterprise level.

You’ll apply Python, AWS, Spark, and Conda across millions of records to extract insights and guide senior leaders, while mentoring a team of analytics professionals in a fast-paced

Qualifications

  • Bachelor’s degree plus 7 years of data analytics experience or Master’s plus 5 years or PhD plus 2 years with expected degree completion by start date.
  • At least 3 years of experience in open source languages for large scale data analysis.
  • At least 3 years of experience with machine learning.
  • At least 3 years of experience with relational databases.

Responsibilities

  • Partner with cross-functional teams to identify and quantify modeling risks.
  • Leverage Python, Conda, AWS, Spark and more to reveal insights and build challenger models.
  • Distill complex modeling systems to influence senior leaders on strategy, use, and risks.
  • Assess and defend state-of-the-art decision-making systems with internal and regulatory partners.
  • Shape the practice of building machine learning models from design through deployment.
  • Oversee development of benchmark and challenger models to stress test critical decisions.

Skills

Open source languages
Machine learning
Relational databases
People management

Education

Bachelor's degree +7 years
Master's degree +5 years
PhD +2 years

Tools

Python
AWS
Spark
Conda
R

Job description

Capital One in Richmond, VA is seeking a Senior Manager, Data Science to lead the Model Risk Office and drive risk-aware data-driven decision making. You’ll partner with data scientists, engineers and product managers to identify model risks, build challenger models, and shape risk strategy at the enterprise level.

You’ll apply Python, AWS, Spark, and Conda across millions of records to extract insights and guide senior leaders, while mentoring a team of analytics professionals in a fast-paced

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