Manager, Data Scientist - Emerging Payments & Airkey

Capital One•New York, NY

27d

About The Position

Manager, Data Scientist - Emerging Payments & Airkey 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 The Emerging Payments organization develops and maintains innovative payment experiences for Capital One customers, including digital wallets, virtual card numbers, merchant checkout experiences, transaction intelligence, and new commercialization opportunities. Our data science team builds machine learning models that help our customers securely facilitate, control, and understand their spend. These models power customer-facing features and experiences that reach tens of millions of customers. We cleanse, enrich, and use large scale card and debit data from Capital One and, more recently, Discover, as well as national metadata datasets around merchants, places, and more. Leveraging the latest approaches and tools, we primarily work with models such as XGBoost, transformers, embeddings, and LLMs, using SQL, Python (and some Scala), tensorflow and pytorch, with Databricks, Snowflake, and other internal platforms and tools. On any given day you’ll be: Creating machine learning models from development through testing and validation to our 30+ million customers in production Designing rich data visualizations to communicate complex ideas to customers or company leaders Investigating the impact of new technologies on the future of mobile banking and the financial world of tomorrow In this role, you will: Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product that customers love Leverage a broad stack of technologies - SQL, Python, Conda, AWS, 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. 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. 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.

Requirements

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

Nice To Haves

PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data science. Bonus points for experience with transformers
At least 4 years of experience in Python, Scala for large scale data analysis
At least 4 years of experience with machine learning
At least 4 years of experience with SQL
At least 1 year of experience working with AWS

Responsibilities

Creating machine learning models from development through testing and validation to our 30+ million customers in production
Designing rich data visualizations to communicate complex ideas to customers or company leaders
Investigating the impact of new technologies on the future of mobile banking and the financial world of tomorrow
Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product that customers love
Leverage a broad stack of technologies - SQL, Python, Conda, AWS, 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

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