Senior Associate, Data Scientist - Business Cards Marketing Data Science

Senior Associate, Data Scientist - Business Cards Marketing Data Science 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. In this role, you will: 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 The Ideal Candidate is: 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. Basic Qualifications: 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 Preferred Qualifications: 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 Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location.

Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York, NY: $148,000 - $168,900 for Sr Assoc, Data Science Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.

Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.

No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace.

Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp.

(COPSSC).