> Markdown version of [/jobs/ext/1653269-manager-data-science-consumer-identity-machine-learning](https://www.wearedevelopers.com/jobs/ext/1653269-manager-data-science-consumer-identity-machine-learning). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Manager, Data Science - Consumer Identity Machine Learning - **Company:** Capital One Financial Corporation - **Location:** San Francisco, CA, United States - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Data Analysis, Big Data, Customer Data Management, Relational Databases, Fraud Prevention and Detection, Mobile Application Software, Python (Programming Language), Machine Learning, Open Source Technology, Sentiment Analysis, SQL Databases, Cloud Platform System, Chatbots, Apache Spark, Deep Learning, Information Technology, Data Analytics - **Published:** July 11, 2026 - **Apply:** https://dejobs.org/x/x/9EC688CA20D44729B80C52146A4E05B4/job/ ## About the Role * Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. * Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. * Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms. * Statistically-minded. You've built models, validated them, and back tested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning. * A data guru. "Big data" doesn't faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science., * Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: * A 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 * A 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 * A 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, * PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics * At least 1 year of experience working with AWS * At least 4 years' experience in Python, Scala, or R for large scale data analysis * At least 4 years' experience with machine learning * At least 4 years' experience with SQL ## Description Consumer Identity ML is the data science and machine learning team inside Capital One's AI foundation organization. We deliver real-time, personalized, intelligent customer experiences in Capital One's suite of award-winning digital products, including our website, mobile app, emails, chatbot, and beyond. We partner closely with our product and engineering teams to build the data and modeling platforms crucial to the deep understanding of customers that enables our applications to delight them by adapting to their needs. As part of Consumer ML, you will: * Explore billions of clickstream events to discover the patterns in customer behavior, and use those patterns to model key customer outcomes * Develop the real-time models that use vast amounts of customer data to anticipate customers' needs and deliver the right options at the right time * Develop the models that ensure our most important customer data is accurate, fighting fraud and other bad behavior, while enabling seamless digital experiences across all our products, In Consumer Identity ML, you will work at all phases of the data science life cycle, including: * Build machine learning models through all phases of development, from design through training, evaluation and validation, and partner with engineering teams to improve operationalization in scalable and resilient production systems that serve 50+ million customers. * Partner closely with a variety of business and product teams across Capital One to conduct the experiments that guide improvements to customer experiences and business outcomes in domains like marketing, servicing and fraud prevention. * Write software (Python, e.g.) to collect, explore, visualize and analyze numerical and textual data (billions of customer transactions, clicks, payments, etc.) using tools like Spark. ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Chatbots are going to destroy infrastructures and your cloud bills](https://www.wearedevelopers.com/videos/1130-chatbots-are-going-to-destroy-infrastructures-and-your-cloud-bills) - [Let's Get Aggregated: Custom UDAFs in Spark ](https://www.wearedevelopers.com/videos/1649-let-s-get-aggregated-custom-udafs-in-spark) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [The Fastest-Growing Tech Sectors to Look Out for in 2025](https://www.wearedevelopers.com/magazine/373-the-fastest-growing-tech-sectors-to-look-out-for-in-2025)