Manager, Data Science – People Tech

Capital One

. Partner with cross-functional data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products .

Posted 9/23/2026full-timeUnited StatesMid-LevelSenior💰 $179,400 - $245,600 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Natural Language Processing, Machine Learning, and Large Language Models, with a strong ability to operationalize models in production environments. Proficient in leveraging cloud computing platforms and open-source tools to deliver AI-powered solutions at scale.

Highest-signal resume keywords

Natural Language ProcessingMachine LearningPython ProgrammingAWS ExperienceModel Risk Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalyticsLarge Language ModelsRelational DatabasesTraining OptimizationSelf-Supervised LearningExplainabilityReinforcement Learning from Human FeedbackModel TrainingModel EvaluationModel Validation

Soft Skills

Cross-Functional CollaborationClear CommunicationStakeholder EngagementTalent DevelopmentInnovative Thinking

Tools & Technologies

PyTorchAWS UltraclustersHugging FaceLangChainLightningVectorDBs

Industry Keywords

AI-Powered ProductsData AnalysisEmerging TechnologiesProduction SystemsQuantitative Field

Tech Stack

Tools & technologies

AWSCloudOpen SourcePythonPyTorchScalaSQL

About the role

Key responsibilities & impact

Partner with cross-functional data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products
Leverage PyTorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and other technologies to analyze numeric and textual data
Apply Natural Language Processing and Large Language Models to customer-facing applications and features
Adapt and fine-tune language models
Build machine learning and NLP models through design, training, evaluation, and validation
Partner with engineering teams to operationalize models in scalable and resilient production systems serving 80+ million customers
Translate complex technical work into tangible business goals
Research and evaluate emerging technologies and state-of-the-art methods
Challenge conventional thinking and improve the status quo with stakeholders
Support talent development for the team and beyond
Influence cross-functional teams in AI/ML innovations
Communicate findings clearly to non-technical audiences

Requirements

What you’ll need

Currently has, or is in the process of obtaining, a Bachelor's Degree in a quantitative field plus 6 years of experience performing data analytics, or a Master's Degree in a quantitative field or MBA with a quantitative concentration plus 4 years of experience, or a PhD in a quantitative field plus 1 year of experience
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
Experience taking models into production through the model risk compliance process
Hands-on experience with LLMs and open-source tools and cloud computing platforms
Experience training language models or large computer vision models
Expertise in one or more of training optimization, self-supervised learning, explainability, or RLHF
Track record of delivering models at scale in training data and inference volumes
Experience delivering libraries, platforms, or solution-level code to existing products
Preferred: PhD in STEM field
Preferred: at least 4 years of machine learning experience
Preferred: at least 4 years of AI modeling experience
Preferred: at least 4 years of experience in Python, Scala, or R
Preferred: at least 4 years of experience with SQL
Preferred: experience working with AWS
Capital One will consider sponsoring a new qualified applicant for employment authorization

Benefits

Comp & perks

Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Comprehensive, competitive, and inclusive health, financial and other benefits supporting total well-being
Reasonable accommodations for applicants who require them
Equal opportunity and non-discrimination protections
Drug-free workplace