Data Science Manager - Apollo Team

Key Skills

AWS, Machine learning techniques, Python Programming, R Programming, Scala Programming, SQL

Job Description

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

Apollo in Card Data Now is Capital One’s one-stop shop for comprehensive, high quality information about businesses in the U.S. utilizing the best of internal and external data sources. Apollo’s mission is to bring together all the disparate needs for business data across the Capital One enterprise and beyond. Apollo delivers data solutions and technology to drive business strategies across the enterprise.

As a Data Scientist on the Apolloteam, you will be responsible for building both batch andreal-time machine learning pipelines to resolve billions of businesses, individuals and transaction records and extract valuable insights. You will collaborate with top notch data scientists, business analysts, product managers, software engineers, data engineers and machine learning engineers to innovate solutions that ultimately impact the company’s bottom line in a meaningful way. You will also have the opportunity to engage with senior leaders from external data companies. You will do it all in a collaborative environment that values your insight, encourages you to take on new responsibilities, promotes continuous learning, and rewards innovation.

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:

• 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.
• 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.
• 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 learnin
• At least 4 years’ experience with SQL
• At least 2 years’ working experience with Entity Resolution/Record Linkage task

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 Science

San Francisco, California (Hybrid On-Site): $213,400 - $243,500 for Mgr, Data Science

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.