Capital One
Manager,DataScientist-Recommendation&PersonalizationSystems
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“Manager, Data Scientist - Recommendation & Personalization Systems at Capital One. Skills: Recommendation & Personalization Systems, Machine Learning, Deep Learning, Transformer-based architectures, Reinforcement Learning, Causal Inference, Data Science. Architecting and deploying cutting-edge personalized recommendation engines. Leveraging high-scale ML models”
What You'll Achieve.
Deliver a product customers love; Unlock the big opportunities that help everyday people save money, time and agony in their financial lives
Industry & Context.
Unlock the big opportunities that help everyday people save money, time and agony in their financial lives; Analyze and create
What They're Looking For.
Must Have
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, 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, 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 Have
PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, 3+ years of hands-on experience building, deploying, and maintaining high-scale, production-grade ML systems using MLOps practices, including AWS, Kubeflow, and CI/CD pipelines, Deep expertise (4+ years) in developing and optimizing state-of-the-art Deep Learning models, specifically Transformer-based architectures, using PyTorch and distributed training with multi-GPU optimization, Extensive experience (4+ years) with high-performance, distributed data processing for petabyte-scale feature engineering using frameworks like DASK and PySpark
What You'll Do.
Architecting and deploying cutting-edge personalized recommendation engines
Leveraging high-scale ML models
Building machine learning models through all phases of development
from design through training
and analyzing data from a variety of sources and structures
How You'll Work.
Team & Collaboration
Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
Communication Scope
Translate the complexity of your work into tangible business goals
Full Job Description
Manager, Data Scientist - Recommendation & Personalization Systems 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:**__ Join an elite Applied AI team within AI Foundations, operating at the intersection of deep research and massive real-world impact. We are pioneering the next generation of personalized customer experiences across Capital One's web and mobile applications, leveraging our high-scale ML models. Our core mission involves architecting and deploying cutting-edge personalized recommendation engines. This is powered by original research into homegrown Foundation Models, advanced Reinforcement Learning techniques, and a state-of-the-art scalable architecture built for billions of interactions. Our research agenda is at the forefront of the field, actively focusing on areas such as Causal Inference, Transformer-based architectures, and sophisticated Recommender Systems. **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 learnin
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