Senior Manager, Data Science - Model Risk

Capital One • McLean, VA

3d • $209,000 - $262,400

About The Position

The Senior Manager, Data Science role is part of Capital One’s Model Risk Office, which works to defend the company against model failures and improve model-based decision-making across Risk Management and the Enterprise. The team combines statistics, software engineering, and business expertise, invests in new skills and tools, and develops techniques to help prevent model failures.

In this role, you will partner with data scientists, software engineers, and product managers to deliver customer-focused products. You will use technologies including Python, Conda, AWS, H2O, and Spark to analyze large volumes of numeric and textual data. You will develop machine learning models through design, training, evaluation, validation, and implementation, and communicate complex work in terms of tangible business goals.

Requirements

• A bachelor's degree in a quantitative field plus 7 years of experience performing data analytics; or a master's degree in a quantitative field or an MBA with a quantitative concentration plus 5 years of data analytics experience; or a 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 working with machine learning.
• At least 2 years of experience utilizing relational databases.

Nice To Haves

• A PhD in a STEM field plus 4 years of experience in data analytics.
• At least 1 year of experience working with AWS.
• At least 1 year of experience managing people or leading team-based projects.
• At least 5 years of experience using Python, Scala, or R for large-scale data analysis.
• At least 5 years of experience with machine learning.

Responsibilities

• Partner with data scientists, software engineers, and product managers to deliver a product customers love.
• Use technologies such as Python, Conda, AWS, H2O, and Spark to uncover insights in large volumes of numeric and textual data.
• Build machine learning models across the development lifecycle, from design through training, evaluation, validation, and implementation.
• Translate complex work into tangible business goals.

Benefits

• Comprehensive health, financial, and other benefits supporting total well-being.
• Eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior