Manager, Data Scientist -Advanced Recommenders and Personalization Systems (Transformers, LLMs & Reinforcement Learning)

Capital One•McLean, VA

8d•Onsite

About The Position

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- We are building the next generation of large-scale reinforcement learning based recommender systems and arbitration engines that will power personalized experiences across marketing, customer servicing, and digital products. This is a high-impact initiative central to our platform, leveraging rich credit and customer behavioral data from tens of millions of customers to deliver intelligent, real-time experiences across our digital experiences, including Mobile, Web, and Email. Why this role: You’ll help shape a foundational system that reaches a vast portion of the U.S. population, influencing how millions of people discover, decide, and engage across financial and lifestyle experiences.

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
Strong background in machine learning, deep learning, and recommender systems.
Hands-on experience with transformers, LLMs, or reinforcement learning.
Experience working with large-scale datasets and distributed training.
Solid programming skills in Python and modern ML frameworks (e.g., PyTorch, TensorFlow).
Ability to translate research into impactful, real-world systems.

Nice To Haves

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
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.

Responsibilities

Design and develop state-of-the-art recommender systems using transformers, large language models (LLMs), and reinforcement learning.
Advance personalization through sequence modeling, multi-modal learning, and contextual decision-making (e.g., contextual Multi-Armed Bandits).
Build and fine-tune foundation models trained on large-scale customer interaction data.
Apply reinforcement learning to optimize long-term user engagement and business outcomes.
Build state-of-the-art evaluation frameworks to measure the efficacy of our campaigns and recommendation systems.
Collaborate with engineering and product teams to deploy scalable, production-grade, low-latency systems.
Drive innovation in emerging areas such as generative recommendations, conversational systems, and cross-domain personalization (e.g., travel, shopping).