Senior Manager, Data Science - Model Risk

Capital One • Richmond, VA

6d

About The Position

Capital One’s Model Risk Office defends the company against model failures and develops ways to improve model-based decisions. The team applies statistics, software engineering, and business expertise to support outcomes in Risk Management and across the Enterprise, while investing in new skills, tools, and trusted partnerships and learning from past mistakes to develop stronger techniques.

The Senior Manager, Data Science partners with data scientists, software engineers, and product managers to deliver customer-focused products. The role uses technologies including Python, Conda, AWS, H2O, and Spark to uncover insights in large volumes of numeric and textual data, and builds machine learning models across design, training, evaluation, validation, and implementation. The role also communicates complex work in terms of tangible business goals and provides leadership, including developing talent and working with stakeholders to improve existing approaches.

The ideal candidate is customer-focused, challenges conventional thinking, evaluates emerging technologies and current research, and has experience building, validating, and backtesting statistical and machine learning models. Capital One will consider sponsoring a qualified applicant for employment authorization. The role is eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives. Capital One also offers a comprehensive set of health, financial, and other benefits; eligibility varies by employment status and management level.

Requirements

• 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. The required degree must be held or in progress with an expectation of completion on or before the scheduled start date.
• 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

• 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.
• 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.
• Experience with clustering, classification, sentiment analysis, time series, and deep learning.

Responsibilities

• Partner with data scientists, software engineers, and product managers to deliver a product customers love.
• Use technologies including Python, Conda, AWS, H2O, and Spark to find insights in large volumes of numeric and textual data.
• Build machine learning models through design, training, evaluation, validation, and implementation.
• Translate complex work into tangible business goals.
• Work with stakeholders to identify and improve the status quo.
• Develop talent on the team and beyond.
• Research and evaluate emerging technologies, stay current on state-of-the-art methods, technologies, and applications, and identify opportunities to apply them.
• Build, validate, and backtest models, applying statistical techniques such as clustering, classification, sentiment analysis, time series, and deep learning.

Benefits

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

What This Job Offers

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