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Manager, Data Scientist - Partnerships AcquisitionsCapital OneChicago, Illinois, United States
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Manager, Data Scientist - Partnerships Acquisitions

Capital One
  • US
    Chicago, Illinois, United States
  • US
    Chicago, Illinois, United States

Über

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:
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 PhD 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:
PhD in “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.
Chicago, IL: $179,400 - $204,700 for Mgr, Data Science
McLean, VA: $197,300 - $225,100 for Mgr, Data Science
New York, NY: $215,200 - $245,600 for Mgr, Data Science
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
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, Article23‑A of the NewYork Correction Law; SanFrancisco, California Police Code Article49, Sections4901‑4920; NewYork 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.
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  • Chicago, Illinois, United States

Sprachkenntnisse

  • English
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