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.
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 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 |
|---|---|---|
| Principal Associate, Data Scientist - LLM Customization Team Capital One's LLM Customization team is seeking a Principal Associate Data Scientist to work on GenAI models. The role involves creating high-quality data for training and testing, building capabilities for evaluating and monitoring generative models, and developing horizontal capabilities like search, summarization, RAG, and agentic workflows for production applications. The candidate will partner with cross-functional teams, leverage technologies like Pytorch, AWS, Hugging Face, LangChain, and VectorDBs, and adapt/finetune LLMs for customer-facing applications. Responsibilities include building ML and NLP models through all development phases, from design to evaluation and validation, and operationalizing them in production systems serving over 80 million customers. Experience in training language models, explainability, RLHF, and delivering models at scale is required. | DataPost-train |
| 8 |
| Principal Associate, Data Scientist - Deposit Forecasting and Pricing This role focuses on developing and supporting econometric time-series models for balance sheet portfolios within Capital One's Retail and Direct Bank. The Data Scientist will apply quantitative methods to improve business performance, demonstrate a track record in behavior model development, and communicate complex models to various stakeholders including management, model risk office, and regulators. The ideal candidate has hands-on experience with data science solutions using open-source tools and cloud platforms, with specific experience in time series, clustering, classification, sentiment analysis, and deep learning. | Data | 7 |
| Principal Associate, Data Scientist - Frontier AI in Customer Protection This role focuses on building knowledge graphs and graph algorithms for fraud prevention within the financial sector. The Data Scientist will leverage technologies like Python, AWS, Spark, Gremlin, and NeptuneDB to uncover hidden connections in data, pilot graph modeling algorithms through development phases, and partner with cross-functional teams to deliver fraud defenses. The ideal candidate is customer-focused, innovative, technically proficient, and skilled in handling large datasets. | Data | 7 |
| Senior Associate, Data Scientist - Cash Flow Underwriting This role focuses on leveraging advanced machine learning techniques to identify and engineer predictive signals from cash flow and transaction data for risk and usage models in the fintech domain. The data scientist will transform raw banking data into high-value features to forecast creditworthiness and customer behavior, building ML models through all phases of development. | Data | 7 |
| Business Manager This Business Manager role focuses on strategic leadership and execution within Capital One's DataLabs Anti-Money Laundering (AML) team. The role involves developing business strategies, managing project delivery, and partnering with various departments to improve compliance and risk management through advanced data methodologies, statistics, and machine learning models. The ideal candidate has a strong quantitative background, experience in developing and validating ML models, and a passion for innovation in the financial services industry. | DataPost-train | 7 |
| Principal Associate, Business Analysis This role focuses on applying advanced data methodologies, statistics, and machine learning models within the Anti-Money Laundering (AML) domain. The Principal Associate, Business Analysis will be responsible for understanding user needs, conducting business analyses, defining business requirements, and executing against product strategy to modernize how Capital One identifies potential financial crimes. While the role involves working with ML models and data, the primary output is business strategy, product definition, and requirements, rather than shipping the ML models themselves. | Data | 5 |
| Principal Associate, Business Analysis The role focuses on modernizing Anti-Money Laundering (AML) processes using advanced analytics, statistics, and machine learning models. It involves developing data sourcing, predictive models, products, monitoring, and reporting. The candidate will understand user needs, conduct business analyses, and translate strategy into tangible products and outcomes within the financial services industry, specifically for AML. | Data | 5 |
| Manager, Data Scientist - Deposit Forecasting and Pricing Manager, Data Scientist role focused on developing behavior models for balance sheet portfolios using econometric time-series models and quantitative methods. The role involves applying machine learning, working with relational databases, and communicating models to stakeholders, including regulators. Requires experience in data analytics, machine learning, and relational databases, with a preference for advanced degrees and Python/Scala/R experience. | Data | 5 |
| Principal Associate, Quantitative Analysis This role involves partnering with business lines to enhance modeling and analytical frameworks, creating novel analytical solutions, and identifying opportunities to apply quantitative methods and automation to improve business performance. The role requires applying expertise in econometric, statistical, and machine learning methods to generate insights and provide technical guidance, with a focus on building cloud-based solutions grounded in data. | Data | 5 |
| Principal Data Analyst, Card Tech Workforce Strategy This role focuses on leveraging AI-driven automation tools like Google Apps Script, Gemini, and Claude Code to build self-service analytics tools for workforce strategy and operations within Capital One's Card Tech division. The primary goal is to enhance operational impact and provide sophisticated analytics for a large global workforce. | Data | 5 |
| Data Annotator The Emerging Technologies Enablement Team (ETE) performs data labeling tasks that support machine learning model and AI development within the Tech organization and across Capital One. This team plays a critical role in reviewing, evaluating, and annotating data to train AI models with the highest quality, accuracy, relevance, fluency, and compliance standards. | Data | 5 |
| Senior Associate, Quantitative Analyst - MLRO Develops and enhances market and counterparty credit risk models for Capital Markets, focusing on Value-at-Risk (VaR), Greeks, PFE, and CVA. The role involves creating novel analytical solutions, applying quantitative methods for business performance improvement, and building cloud-based solutions. Requires strong quantitative analysis skills, proficiency in scripting languages like Python, and experience in econometric analysis and machine learning. | Data | 5 |
| Intern, Data Scientist - Fall 2026 Intern Data Scientist role at Capital One Canada focusing on leveraging model solutions to solve complex business problems, including fraud detection, customer behavior prediction, financial risk modeling, and search engine marketing optimization. The role involves end-to-end project ownership from problem identification to solution deployment, with responsibilities in data analysis, predictive modeling, and data pipeline development. | Data | 5 |
| Senior Quantitative Analyst - Global Finance This role focuses on quantitative analysis and modeling within Capital Markets & Analytics, applying machine learning and statistical methods to financial problems like derivatives and fixed income. It involves developing and enhancing analytical frameworks, creating novel solutions, and collaborating on cloud-based data solutions. The position requires expertise in quantitative methods, programming (Python/R/SQL), and communicating complex results. | Data | 5 |
| Senior Quantitative Analyst - Global Finance This role focuses on developing and enhancing quantitative models and analytical frameworks within Capital Markets & Analytics, leveraging machine learning and cloud technologies to manage financial risks and drive business insights in the fintech domain. The position requires expertise in quantitative analysis, statistical modeling, and programming, with a focus on applying these skills to financial markets, derivatives, and investment portfolios. | Data | 5 |
| Distinguished Data Engineer Distinguished Data Engineer role focused on driving technical strategy for enterprise-scale data pipelines, leveraging AWS, Lakehouse architecture, Kafka, Flink, Spark, Airflow, Snowflake, and Databricks. The role involves building awareness, promoting engineering excellence, influencing stakeholders, and mentoring talent. Preferred qualifications include experience deploying ML models and Agentic AI solutions, and data observability tooling. | DataAgent | 5 |
| Distinguished Software Data Engineer This role focuses on designing and architecting Capital One's enterprise data platforms, with a specific emphasis on creating a unified Data Product architecture to ensure AI readiness. The goal is to transform fragmented datasets into high-fidelity, machine-ready assets by modernizing the Business Data Catalog and driving data standardization practices. The engineer will build resilient, distributed systems and event-driven patterns, acting as an authoritative expert in data consumption and a visionary builder. | Data | 5 |
| Senior Business Analyst - Anti-Money Laundering (AML) Modeling The Anti-Money Laundering (AML) Modeling and Advanced Data Insights team is modernizing how Capital One identifies potential money laundering, terrorist financing, and human trafficking through advanced analytic techniques, statistics, and machine learning models. The team develops data sourcing, predictive models, monitoring, and reporting using tools like AWS, Snowflake, Python, and Spark. The role is responsible for end-to-end development, deployment, and monitoring of critical risk management models. | Data | 5 |
| Principal Associate, Data Scientist - Anti-Money Laundering Modeling and Advanced Data Insights The Anti-Money Laundering (AML) Modeling and Advanced Data Insights team at Capital One is modernizing the identification of financial crimes using advanced analytics, statistics, and machine learning. The role involves developing predictive models, monitoring dashboards, and reporting using tools like AWS, Snowflake, Python, and Spark. The team is responsible for the end-to-end development, deployment, and monitoring of production models for transaction monitoring with machine learning, including Generative AI models. | Data | 5 |
| Director, Data Scientist - External Data Strategy This role is for a Director of Data Science focused on External Data Strategy within Capital One's fintech domain. The position involves leading a team of 10-15 data scientists, building machine learning models and data pipelines, and leveraging technologies like Python, Spark, Databricks, and AWS. The primary focus is on data lifecycle management, from sourcing to feature engineering and model implementation, to understand customer financial lives and drive business decisions. The role requires strong leadership, technical expertise in data science and machine learning, and experience with large-scale data analysis and relational databases. | Data | 5 |