Senior Data Scientist, The Recommendation & Personalization Team

San Jose (61069), United States of America, SAN JOSE, California

Senior Data Scientist, The Recommendation & Personalization Team

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 Recommendation & Personalization team in AI Foundations builds state of the art scalable AI/ML solutions for Capital One’s award-winning mobile app, website, emails, and other digital channels. We partner with product, tech, and design teams to deliver features that delight customers with personalized recommendations and experiences. You will be the driving force to experiment, innovate and create next generation experiences powered by the latest emerging AI/ML technologies. Our areas of research include reinforcement learning, recommender systems, causal inference, and multi-objective learning with transformers. 

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, AWS, Pyspark, Nvidia Rapids / Merlin / Triton, 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.

• 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.

• 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.

• 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 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 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 2 years of experience in data analytic

  • 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 

• At least 1 year of experience in open source programming languages for large scale data analysis

• At least 1 year of experience with machine learning