Manager, Data Science – AI Foundations

Capital One

Data science manager building scalable LLM and NLP products for Capital One’s mobile app. Leading AI-powered customer experiences across Capital One’s massive data platform.

Posted 9/4/2026full-timeNew York City • California, New York, Virginia • 🇺🇸 United StatesJunior💰 $197,300 - $245,600 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and operationalizing AI and machine learning solutions, with a strong focus on natural language processing and large language models. Proven ability to translate complex technical concepts into actionable business strategies while collaborating with cross-functional teams.

Highest-signal resume keywords

Machine Learning ExpertiseNatural Language Processing (NLP)Experience with PyTorchProficiency in PythonExperience with AWS

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalyticsModel Training and EvaluationRelational DatabasesLarge-Scale Data AnalysisTraining OptimizationSelf-Supervised LearningExplainabilityReinforcement Learning from Human Feedback (RLHF)SQLCloud Computing

Soft Skills

Cross-Functional CollaborationInfluencing StakeholdersCommunication SkillsTalent Development

Tools & Technologies

AWS UltraclustersHugging FaceLangChainLightningVectorDBs

Certifications & Qualifications

Bachelor's Degree in Quantitative FieldMaster's Degree in Quantitative Field or MBAPhD in Quantitative Field

Industry Keywords

AI-Powered ProductsCustomer ExperienceDigital AssistantEmerging TechnologiesScalable Architecture

Tech Stack

Tools & technologies

AWSCloudPythonPyTorchScalaSQL

About the role

Key responsibilities & impact

Partner with data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products
Build and ship scalable architecture and AI/ML solutions for Capital One’s mobile app
Develop app features with dynamic and personalized customer experiences
Enable customers to interact with digital assistant Eno and search useful content
Leverage PyTorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and other technologies to analyze numeric and textual data
Apply NLP and LLM expertise to adapt and fine-tune models for customer-facing applications
Build machine learning and NLP models through design, training, evaluation, and validation
Partner with engineering teams to operationalize models in scalable, resilient production systems serving 80+ million customers
Translate complex technical work into tangible business goals
Research and evaluate emerging technologies and apply state-of-the-art methods
Lead talent development for the team and beyond
Influence cross-functional stakeholders and communicate findings to non-technical audiences

Requirements

What you’ll need

Currently has, or is in the process of obtaining, a required degree with expected completion by the scheduled start date
Bachelor's Degree in a quantitative field plus 6 years of experience performing data analytics, OR Master's Degree in a quantitative field or MBA with a quantitative concentration plus 4 years of experience performing data analytics, OR PhD in a 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
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
Hands-on experience with LLMs and solutions using open-source tools and cloud computing platforms
Preferred: PhD in a STEM field
Preferred: Experience working with AWS
Preferred: At least 4 years of experience in Python, Scala, or R
Preferred: At least 4 years of experience with machine learning
Preferred: At least 4 years of experience with SQL
Capital One will consider sponsoring a new qualified applicant for employment authorization

Benefits

Comp & perks

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