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Principal Associate, Data Scientist - Card IntelligenceCapital One National Association • New York, New York, United States
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Principal Associate, Data Scientist - Card Intelligence

Capital One National Association
  • US
    New York, New York, United States
  • US
    New York, New York, United States
Jetzt Bewerben

Über

Principal Associate, Data Scientist - Card Intelligence 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 relational databases, 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 hardship in their financial lives.
Team Description The US Card Data Science organization at Capital One leverages our massive wealth of customer data to drive business strategy and deliver world‑class customer experiences. Our team builds and deploys sophisticated data science and machine learning models across the entire credit card lifecycle—including marketing, acquisitions, underwriting, and fraud prevention. In this role, you will turn complex insights into real‑world impact, shaping financial products that serve and protect millions of cardholders daily.
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 your interpersonal skills to translate the complexity of your work into tangible business goals.
Ideal Candidate
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.
Innovative. You continually research and evaluate emerging technologies. You stay current on published state‑of‑the‑art methods, technologies, and applications and seek out opportunities to apply them.
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.
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 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 five 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 three years of experience performing data analytics.
A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field).
Preferred Qualifications
Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus three years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics).
At least one year of experience working with AWS.
At least three years’ experience in Python, Scala, or R.
At least three years’ experience with machine learning.
At least three years’ experience with SQL.
Compensation Minimum and maximum full‑time annual salaries for this role are listed below, by location. Salaries for part‑time roles will be prorated. McLean, VA: $161,800 – $184,600; New York, NY: $176,500 – $201,400. Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary offered to any candidate will be reflected solely in the 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.
Benefits Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well‑being.
Employment Considerations Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Equal Opportunity Capital One is an equal‑opportunity employer (EOE, including disability/vet) committed to non‑discrimination in compliance with applicable federal, state, and local laws.
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  • New York, New York, United States

Sprachkenntnisse

  • English
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