Manager, Data Scientist - Partnerships Acquisitions

Manager, Data Scientist - Partnerships Acquisitions 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 Partnerships Acquisitions Data Science team builds the machine learning models that help our co‑branded card customers. We prioritize advanced modeling techniques, alternative data sources, and robust infrastructure to enhance decision accuracy and efficiency. The associate is responsible for leading a workstream building the next generation of machine learning models used for credit decisioning. These models will be used for critical business decisions, such as card application approve/decline, product optimization, customer valuation, and more. Role Description In this role, you will: 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 your interpersonal skills to translate the complexity of your work into tangible business goals The Ideal Candidate is: Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond. Technical. You’re comfortable with open‑source languages and are passionate about developing further. You have hands‑on experience developing data science solutions using open‑source tools and cloud computing platforms. Statistically‑minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning. 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 6 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 plus 4 years of experience performing data analytics A Ph.D. in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics 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 Preferred Qualifications Ph.D. in a STEM field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data science/machine learning At least 1 year of experience working with AWS At least 4 years’ experience in Python, Scala, or R for large‑scale data analysis At least 4 years’ experience with machine learning At least 4 years’ experience with SQL 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 by location. Salaries for part‑time roles will be prorated based on the agreed‑upon number of hours to be regularly worked: Chicago, IL: $179,400 – $204,700 McLean, VA: $197,300 – $225,100 New York, NY: $215,200 – $245,600 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. 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. #J-18808-Ljbffr Hobbsnews