Manager, Data Scientist

About the Role

Data is at the center of everything we do at Capital One. As a Data Scientist, you’ll be part of a team leading the next wave of disruption, using the latest computing and machine learning technologies and operating across billions of customer records.

Join an elite Applied AI team within AI Foundations, operating at the intersection of deep research and massive real-world impact. We are pioneering the next generation of personalized customer experiences across Capital One's web and mobile applications, leveraging our high-scale ML models. Our core mission involves architecting and deploying cutting-edge personalized recommendation engines, powered by original research into homegrown Foundation Models, advanced Reinforcement Learning techniques, and a state-of-the-art scalable architecture built for billions of interactions. Our research agenda is at the forefront of the field, actively focusing on areas such as Causal Inference, Transformer-based architectures, and sophisticated Recommender Systems.

Key Responsibilities

• Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love.
• Leverage a broad stack of technologies - Python, Conda, AWS, H2O, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data.
• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation.
• Flex interpersonal skills to translate the complexity of your work into tangible business goals.

Requirements & Tech Stack

• Currently have, or be in the process of obtaining, a degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field).
• 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.

Qualifications

• Customer first: Passion for analyzing and creating, with a focus on making the right decision for customers.
• Innovative: Continually research and evaluate emerging technologies; stay current on published state-of-the-art methods and applications.
• Creative: Thrive on bringing definition to big, undefined problems; enjoy asking questions and pushing hard to find answers; willing to share new ideas.
• A leader: Challenge conventional thinking and work with stakeholders to improve the status quo; passionate about talent development.
• Technical: Comfortable with open-source languages; hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
• Statistically-minded: Experience building, validating, and backtesting models; knowledge of interpreting confusion matrices or ROC curves; experience with clustering, classification, sentiment analysis, time series, and deep learning.
• A data guru: Comfortable with "big data"; skills to retrieve, combine, and analyze data from a variety of sources and structures.

Experience Levels & Degrees

• Bachelor's Degree in a quantitative field + 6 years of experience performing data analytics.
• Master's Degree in a quantitative field or an MBA with a quantitative concentration + 4 years of experience performing data analytics.
• PhD in a quantitative field + 1 year of experience performing data analytics.

Preferred Qualifications

• PhD in “STEM” field + 3 years of experience in data analytics.
• At least 4 years of experience in 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.
• At least 1 year of experience working with AWS.