Principal Associate, Data Scientist - Card...
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Role details
Tech stack
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Requirements
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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
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Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
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Flex your interpersonal skills to translate the complexity of your work into tangible business goals
The Ideal Candidate is:
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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 itâs about making the right decision for our customers.
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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.
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Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. Youâre not afraid to share a new idea.
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A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. Youâre passionate about talent development for your own team and beyond.
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Technical. Youâre 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.
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Statistically-minded. Youâve 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.
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A data guru. âBig dataâ doesnât 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:
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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:
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A Bachelorâs Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics
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A Masterâs 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 3 years of experience performing data analytics
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A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)
Preferred Qualifications:
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Masterâs Degree in âSTEMâ field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in âSTEMâ field (Science, Technology, Engineering, or Mathematics)
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At least 1 year of experience working with AWS
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At least 3 yearsâ experience in Python, Scala, or R
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At least 3 yearsâ experience with machine learning
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At least 3 yearsâ 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 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.
Cambridge, MA: $161,800 - $184,600 for Princ Associate, Data Science
About the company
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., 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., 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 (https://www.capitalonecareers.com/benefits) . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level., 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).
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