Senior Associate, Data Scientist - Business Cards Marketing Data Science

Capital One • New York, NY

3d • $148,000 - $168,900

About The Position

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. Team Description: The Business Cards Marketing Data Science Team is a team of talented data scientists leveraging cutting-edge machine learning models and statistical methods to deeply understand customer behavior, so we can optimize our marketing campaigns to win new customers and drive sticky relationships with our existing customers. In the recent past, we have experimented with multiple modeling approaches including time-series models, regression & classification models, ensemble models, LLMs, causal learners to name a few. Our objective is to drive model usage across every aspect of marketing and increase personalization. We are embedded within the teams owning the campaigns and hence work very closely with business analysts and marketers to ensure that the models we build drive business value and are used in decision making and in marketing campaigns.

Requirements

• Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics
• A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration
• Technical. You have hands-on experience building machine learning models for real world use cases. You are fluent in Python, SQL and command line. You write readable and efficient code from the get-go. You know how to work with messy data sources.
• Statistically-minded. You understand statistical concepts like multiple testing, causal inference, bias, etc. You have experience with building and diagnosing different types of machine learning models (eg. classification, clustering, time series). You are keen on staying current in your understanding of modern machine learning models including Gen AI.
• A strong communicator with solid written and verbal communication skills. Your documentation clearly articulates your thinking and you can communicate results well to your peers and other technical and business leaders.
• A self-starter and a creative problem solver. You take initiative, iterate quickly, know how to move past challenges and find innovative solutions to business problems.

Nice To Haves

• Master's Degree or PhD in Statistics, Mathematics, Computer Science, Data Science or other relevant technical disciplines
• 2+ years of experience with Python, SQL, and scripting
• 2+ years of experience working with and analyzing large datasets using quantitative approaches
• 2+ years of experience building, analyzing, and deploying machine learning models

Responsibilities

• Build and maintain machine learning models end-to-end, validate models for different business use cases and conduct rigorous statistical analyses of various business strategies
• Present findings to technical and business stakeholders and make appropriate recommendations
• Partner with a cross-functional team of data scientists, business analysts, marketers, product managers and software engineers to deliver a product customers love
• Leverage a broad stack of technologies - Python, SQL & Enterprise tools - to train models and conduct analyses

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees