Senior Manager, Data Science - Model Risk

Capital One • McLean, VA

3d • $209,000 - $286,200

About The Position

As a Data Scientist at Capital One, you will work in the Model Risk Office, helping defend the company against model failures and develop better model-driven decisions for Risk Management and the Enterprise. You will contribute to a cross-functional team and use statistical, software engineering, and business expertise to deliver customer-focused products and outcomes.

You will use technologies including Python, Conda, AWS, H2O, and Spark to analyze large volumes of numeric and textual data. You will build machine learning models throughout the development lifecycle, from design and training through evaluation, validation, and implementation, and translate technical work into tangible business goals. The role also calls for leadership, talent development, customer focus, and ongoing evaluation of emerging technologies and state-of-the-art methods.

The role offers location-dependent full-time annual salary ranges: McLean, Virginia, $229,900–$262,400; New York, New York, $250,800–$286,200; Richmond, Virginia, $209,000–$238,500; and Riverwoods, Illinois, $209,000–$238,500. It is also eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives. Capital One describes its benefits as a comprehensive, competitive, and inclusive set of health, financial, and other benefits; eligibility varies by employment and management status.

Requirements

• Currently hold, or be in the process of obtaining by the scheduled start date, 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 using 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.

Responsibilities

• Partner with data scientists, software engineers, and product managers to deliver customer-focused products.
• Use technologies such as 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 technical work into tangible business goals.
• Challenge conventional thinking and work with stakeholders to identify and improve existing practices.
• Support talent development for the team and beyond.
• Research and evaluate emerging technologies, methods, and applications.
• Build, validate, and backtest statistical models, applying methods such as clustering, classification, sentiment analysis, time series, and deep learning.

Benefits

• Comprehensive, competitive, and inclusive health, financial, and other benefits.
• Performance-based incentive compensation, potentially including cash bonuses and/or long-term incentives.

What This Job Offers

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