NYC 299 Park Avenue (22957), United States of America, New York, New York
Senior Manager, Data Science - Business Card & Payments
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
Business Card & Payments Data Science team builds industry leading machine learning models to empower credit underwriting decisionings, supports advancement in Capital One business card product strategies, decisioning and credit infrastructures. This team builds full-rounded modeling solutions across customer life cycles, with strong collaborations and engagement with business stakeholders, cross functional partnerships including tech and data engineers, to problem solve and develop modeling strategy and solutions with innovative approach.
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:
- Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
- 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.
- A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.
Basic Qualifications:
- Currently has, or is in the process of obtaining a Bachelor’s Degree plus 7 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining PhD plus 2 years of experience in data analytics, with an expectation that required degree will be obtained on or before the scheduled start date
- At least 3 years’ experience in open source programming languages for large scale data analysis
- At least 3 years’ experience with machine learning
- At least 3 years’ experience with relational databases
Preferred Qualifications:
- PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics
- At least 1 year of experience working with AWS
- At least 1 year of experience managing people
- At least 5 years’ experience in Python, Scala, or R for large scale data analysis
- At least 5 years’ experience with machine learning
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 City (Hybrid On-Site): $234,700 - $267,900 for Sr Mgr, 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 . 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace.
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 . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
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