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Manager, Data Scientist - Business Card & Payments

Capital One

McLean · On-site Part-time Executive $201k – $230k/yr 3w ago

About the role

NYC 299 Park Avenue (22957), United States of America, New York, New YorkManager, Data Scientist - Business Card & PaymentsData 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:

• 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.

• 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 a Bachelor’s Degree plus 6 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 4 years of experience in data analytics, or currently has, or is in the process of obtaining PhD plus 1 year of experience in data analytics, with an expectation that required degree will be obtained on or before the scheduled start date

• 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.

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): $201,400 - $229,900 for Mgr, Data ScienceCandidates

Requirements

  • 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 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
  • 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
  • Currently has, or is in the process of obtaining a Bachelor’s Degree plus 6 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 4 years of experience in data analytics, or currently has, or is in the process of obtaining PhD plus 1 year of experience in data analytics, with an expectation that required degree will be obtained on or before the scheduled start date
  • 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

Responsibilities

  • 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
  • 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
  • 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
  • You’ve built models, validated them, and backtested them

Benefits

Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked

Skills

PythonCondaAWSH2OSparkMachine learningData analysisRelational databasesSQL

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