Currently tracking 241 active AI roles, down 26% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $123k–$392k (avg $231k).
Capital One currently has 293 active AI-related job listings. The majority of these roles are focused on serving infrastructure, accounting for 28% of the total, followed closely by agents at 26% and post-training at 23%. Engineering is the dominant function, with 234 roles, and hiring is primarily concentrated in the United States. Frequent tech tags include model_serving, vector_db, and llm_observability, suggesting a focus on the operational aspects of AI deployment. In the last 30 days, Capital One posted 124 new AI roles, representing a 22% increase compared to the previous 30-day period.
Capital One currently has 305 active AI-related roles in our index. The most common open titles are: Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) (9), Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) (8), Applied Researcher I (6), Distinguished Engineer (6), Applied Researcher II (5). Most positions are in Engineering and Research.
Capital One's active AI hiring is concentrated in: serving infrastructure (28%), agents (27%), post-training (23%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Capital One is hiring AI talent in: United States (299 roles), United Kingdom (3 roles), Canada (2 roles), Philippines (1 role).
Job postings at Capital One most frequently reference: model serving, vector db, fine tuning, llm observability, inference infra.
In the past 30 days, Capital One has posted 96 new AI-related roles. That is a -26% change versus the prior 30 days (130 → 96).
| Title | Stage | AI score |
|---|---|---|
| Manager, Data Science - Consumer Identity Machine Learning Manager of Data Science for Consumer Identity Machine Learning team within Capital One's AI foundation organization. The role focuses on delivering real-time, personalized customer experiences by building and operationalizing machine learning models that use vast amounts of customer data to anticipate needs, fight fraud, and improve digital experiences. The role involves working across the data science lifecycle, from design and training to evaluation and production deployment, partnering with product and engineering teams to serve over 50 million customers. | Post-trainServe | 7 |
| Manager, Data Science - Emerging ML Capital One's Emerging ML team is seeking a Manager, Data Science to conduct research and development in AI, focusing on embeddings and foundation models. The role involves building machine learning models from design through production, partnering with product and engineering teams, and analyzing large-scale customer data using tools like Spark and AWS. The ideal candidate is curious, technical, statistically-minded, and customer-oriented, with hands-on experience in data science lifecycle and open-source tools. |
| Post-trainServe |
| 7 |
| Principal Associate, Data Science - US Card Fraud Authentication Team Data Scientist role focused on building and implementing machine learning models for fraud detection and authentication within the US Card Fraud Authentication team. The role involves analyzing complex datasets, optimizing authentication decisioning, and staying ahead of evolving fraud patterns using a modern tech stack including Python, AWS, Spark, H2O, and SQL. | Post-trainData | 7 |
| Principal Associate, Data Scientist - US Card DFS Acquisitions This role focuses on building and deploying machine learning models for credit card customer acquisitions within the fintech domain. The data scientist will own the full model lifecycle, from design and training to evaluation, validation, implementation, monitoring, and governance. The role involves leveraging Python, AWS, Spark, and H2O to analyze large datasets and develop models for underwriting decisions. | Post-train | 7 |
| Manager, Data Science - LLM Customization Team Capital One is seeking a Manager, Data Science to lead the LLM Customization team, focusing on bringing LLMs and GenAI to life within the company. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch, Hugging Face, and LangChain, and specializing in NLP for LLM adaptation and fine-tuning. Responsibilities include building NLP models through development, training, evaluation, and validation, and operationalizing them in production systems. The ideal candidate is innovative, creative, technical, and influential, with experience in training language models, large computer vision models, and delivering models at scale. | Post-trainServe | 7 |
| Principal Data Scientist Capital One is seeking a Principal Data Scientist to build and implement machine learning models for real-time credit underwriting decisions within their Business Card & Payments team. The role involves leveraging Python, AWS, and Spark to develop models from design through implementation, working with large datasets, and translating complex work into business goals. Experience with classification, sentiment analysis, time series, and deep learning is expected. | Post-trainServe | 7 |
| Senior Associate, Data Scientist Data Scientist role focused on modernizing loss forecasting and data transformation within Capital One's credit risk management team. The role involves building statistical/machine learning models to challenge existing production models, contributing to model governance, and presenting model risks to executives. Requires experience with Python, AWS, Spark, and machine learning, with a strong statistical background and ability to handle large datasets. | Post-train | 7 |
| Senior Associate, Data Scientist - Financial Services Data Scientist role at Capital One's Auto Finance business, focusing on building machine learning models for applications like customer lifetime valuation, product recommendation, fraud detection, and marketing optimization. The role involves leveraging technologies like Python, AWS, and Spark, and working through all phases of model development from design to implementation. | Post-train | 7 |
| Principal Data Scientist Capital One's DataLabs AML team is modernizing money laundering detection using advanced analytics, statistics, and machine learning models. This Principal Data Scientist role involves end-to-end development, deployment, and monitoring of risk management models, partnering cross-functionally, and defending these systems to regulators. The role requires strong ML/statistical skills, experience with Python/R, and SQL, with a focus on building and validating predictive models in the financial services domain. | Post-train | 7 |
| Principal Associate, Data Scientist - AI for Data Data Scientist role focused on developing AI-enabled features across the data lifecycle within a fintech company. Responsibilities include building ML models through all phases, leveraging technologies like Python, AWS, and Spark, and collaborating with cross-functional teams. Requires experience with various ML techniques, deep learning frameworks, and NLP/IR/Search/Recommendations/Fine-tuning on LLMs. | Post-trainServe | 7 |
| Senior Manager, Data Science - Cash Flow Underwriting Senior Manager, Data Science for Cash Flow Underwriting at Capital One. This role focuses on leveraging advanced machine learning techniques to build and implement predictive models for risk and usage, transforming raw banking data into valuable features for forecasting creditworthiness and customer behavior. The role involves leading a team, strategic planning, and end-to-end model development. | Post-train | 7 |
| Principal Associate, Data Scientist - Mainstreet Acquisitions Capital One is seeking a Principal Associate, Data Scientist for their Mainstreet Acquisitions team. This role involves developing and deploying valuation models for credit underwriting, leveraging alternative data sources and advanced modeling techniques. The position requires building machine learning models through all phases of development, from design through training, evaluation, validation, and implementation, using technologies like Python, AWS, and Spark. The ideal candidate is customer-focused, innovative, creative, technically proficient, statistically-minded, and skilled in handling large datasets. | Post-train | 7 |
| Manager, Data Scientist - Credit Review Manager, Data Scientist role at Capital One focused on challenging existing production models with new statistical and machine learning models. The role involves leveraging technologies like Python, AWS, H2O, and Spark to analyze large volumes of data, build and validate models, and collaborate with cross-functional teams. The ideal candidate has a strong statistical background, experience with various machine learning techniques, and a passion for innovation. | Post-train | 5 |
| Senior Manager, Quantitative Analysis - Model Risk Office Senior Manager role focused on quantitative analysis within the Model Risk Office at Capital One. The role involves partnering with model development and risk teams to advance the Loan Loss Forecasting and ACL framework, assessing model design, and ensuring model quality and transparency. Requires strong experience in statistical and machine learning modeling, Python/R, and communicating technical concepts to various stakeholders, including regulators. | Post-train | 5 |
| Manager, Data Scientist - Upmarket Acquisitions Valuations Capital One is seeking a Manager, Data Scientist to lead the Valuations Infrastructure pod within the Upmarket Acquisitions team. This role involves building and implementing machine learning models for credit card valuations, impacting millions of accounts and billions in exposure annually. The position requires strong technical skills in data analysis, machine learning, and open-source tools, with a focus on translating complex work into tangible business goals within a regulated fintech environment. | Post-train | 5 |
| Manager, Data Scientist - Bureau Data Strategy Capital One is seeking a Manager, Data Scientist for their Bureau Data Strategy team. This role involves partnering with cross-functional teams to deliver products, leveraging technologies like Python, AWS, and Spark to analyze large datasets, and building machine learning models through all phases of development. The ideal candidate is customer-focused, a leader, technically proficient, and a data expert with experience in open-source tools and cloud platforms. | Post-train | 5 |
| Senior Manager, Data Scientist - Card DFS Integration This role is for a Senior Manager, Data Scientist focused on Card DFS Integration within Capital One's Discover Card Customer Management Data Science team. The role involves partnering with cross-functional teams, leveraging technologies like Python, AWS, and Spark, and building machine learning models through all phases of development. The ideal candidate is customer-focused, creative, statistically-minded, and proficient with large datasets and various machine learning techniques including clustering, classification, sentiment analysis, time series, and deep learning. | Post-train | 5 |
| Senior Associate, Data Scientist - Credit Line Increase Program This role focuses on building and deploying machine learning models for credit line increases within a fintech company. The data scientist will work across the full model lifecycle, from design and training to evaluation and implementation, leveraging various technologies and collaborating with cross-functional teams. The role emphasizes innovation, technical skills in data science solutions, and statistical modeling. | Post-train | 5 |
| Manager, Data Science - PULSE Network, Business Intelligence Manager, Data Science role at Capital One focused on Business Intelligence and pricing strategy optimization. The role involves leveraging machine learning models throughout their development lifecycle, from design to implementation, using technologies like Python, AWS, H2O, and Spark. The ideal candidate is innovative, creative, statistically-minded, and proficient with large datasets and relational databases. | Post-train | 5 |
| Principal Associate, Data Scientist - Retail Bank Marketing This role focuses on building and operating machine learning models for retail bank marketing, optimizing marketing spend, product recommendations, and new account value estimation. It involves data and model pipelining, machine learning, and model operations using Python and ML libraries. The role also explores next-generation model architectures like embeddings and sequence models. | Post-train | 5 |