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R118503 Posted 09/14/2021

Data Science Manager, Digital ML

Cambridge , Massachusetts | Richmond , Virginia | Vienna , Virginia | New York , New York
  • Category Data Science
  • Experience Manager
  • Primary Address Cambridge, Massachusetts

Overview

314 Main Street (21020), United States of America, Cambridge, Massachusetts

Data Science Manager, Digital ML

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

Digital ML is the data science and machine learning team inside Capital One’s Digital Products organization.  We deliver real-time, personalized, intelligent customer experiences in Capital One’s suite of award-winning digital products, including our website, mobile app, emails, chatbot, and beyond.  We partner closely with our product and engineering teams to build the data and modeling platforms crucial to delighting a combined 52 million customers each month and empowering them to manage their financial lives digitally.

As part of Digital ML, you will work on things like:

  • The servicing optimization engine that anticipates customers’ needs in real time and helps them manage their accounts, purchases, payments, rewards, and more 

  • The marketing optimization engine that selects the right offer for the right customer

  • The experimentation engine that enables us to rigorously test new features, messaging and offers for our customers

  • Customer behavioral analyses (using transaction, clickstream and other data) that identify trends, patterns and relationships related to product usage 

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, Pytorch, and more — to reveal the insights hidden within huge volumes of structured and unstructured 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:

  • 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.

  • 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 back tested 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:

  • Bachelor’s Degree plus 6 years of experience in data analytics, or Master’s Degree plus 4 years of experience in data analytics, or PhD plus 1 year of experience in data analytics

  • At least 2 years’ experience in open source programming languages for large scale data analysis

  • At least 2 years’ experience with machine learning

  • At least 2 years’ experience with relational databases

Preferred Qualifications:

  • PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics

  • 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.

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, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. 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, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York 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.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

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).

Hiring Process
Stories
Benefits
Career Journey

How We Hire

We take finding great coworkers pretty seriously.

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  • Step 1 Apply

    It only takes a few minutes to complete our application and assessment.

  • Step 2 Screen and Schedule

    If your application is a good match you’ll hear from one of our recruiters to set up a screening interview.

  • Step 3 Interview(s)

    Now’s your chance to learn about the job, show us who you are, share why you would be a great addition to the team and determine if Capital One is the place for you.

  • Step 4 Decision

    The team will discuss — if it’s a good fit for us and you, we’ll make it official!

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How to Pick the Perfect Career Opportunity

Overwhelmed by a tough career choice? Read these tips from Devon Rollins, Senior Director of Cyber Intelligence, to help you accept the right offer with confidence.

Your wellbeing is our priority

Our benefits and total compensation package is designed for the whole person. Caring for both you and your family.

  • Healthy Body, Healthy Mind

    You have options and we have the tools to help you decide which health plans best fit your needs.

  • Save Money, Make Money

    Secure your present, plan for your future and reduce expenses along the way.

  • Time, Family and Advice

    Options for your time, opportunities for your family, and advice along the way. It’s time to BeWell.

Career Journey

Here’s how the team fits together. We’re big on growth and knowing who and how coworkers can best support you.

Career Journey
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