Manager, Data Scientist - Alternative Data Strategy

Capital One • McLean, NY

23h • Hybrid

About The Position

The Alternative Data Strategy team advances credit decisioning by integrating non-traditional datasets into US Card strategies. The Manager, Data Scientist evaluates emerging vendors and data products, engineers impactful features, builds scalable data processing and monitoring systems, and acts as a data domain expert who guides users on dataset applications. The role also involves navigating risk governance for vendor models and building challenger models using new data to enhance existing models, with extensive cross-functional collaboration.

The position partners with data scientists, software engineers, and product managers to deliver customer-focused products. It uses technologies such as Python, Conda, AWS, H2O, and Spark to analyze large volumes of numeric and textual data, and develops machine learning models throughout design, training, evaluation, validation, and implementation. The role translates technical work into tangible business goals. It is hybrid, subject to Capital One’s policy for required on-site presence at the designated office location.

Requirements

• A bachelor’s degree in a quantitative field and 6 years of experience performing data analytics; or a master’s degree in a quantitative field or an MBA with a quantitative concentration and 4 years of data analytics experience; or a PhD in a quantitative field and 1 year of data analytics experience. The required degree must be obtained on or before the scheduled start date.
• At least 1 year of experience leveraging open-source programming languages for large-scale data analysis.
• At least 1 year of experience working with machine learning.
• At least 1 year of experience utilizing relational databases.
• Hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
• Experience building, validating, and backtesting models, and interpreting confusion matrices or ROC curves.
• Experience with clustering, classification, sentiment analysis, time series, and deep learning.
• Ability to retrieve, combine, and analyze data from a variety of sources and structures.

Nice To Haves

• PhD in a STEM field plus 3 years of experience in data analytics.
• At least 1 year of experience working with AWS.
• At least 4 years of experience using Python, Scala, or R for large-scale data analysis.
• At least 4 years of experience with machine learning.
• At least 4 years of experience with SQL.

Responsibilities

• Evaluate emerging alternative-data vendors and data products.
• Engineer high-impact features and build scalable data processing and monitoring systems.
• Serve as the data domain expert and guide users on dataset applications.
• Navigate risk governance for vendor models and build challenger models using new data.
• Partner with data scientists, software engineers, and product managers to deliver customer-focused products.
• Use technologies including Python, Conda, AWS, H2O, and Spark to analyze large volumes of numeric and textual data.
• Develop machine learning models through design, training, evaluation, validation, and implementation.
• Translate complex technical work into tangible business goals.

Benefits

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

What This Job Offers

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