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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Princ Associate, Data Science - **Company:** Capital One Financial Corporation - **Location:** Chicago, IL, United States - **Salary:** $147,100.0 - $167,900.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Python (Programming Language), Machine Learning, Open Source Technology, Performance Tuning, Standard Sql, Sentiment Analysis, Cloud Platform System, Large Language Models, Snowflake, Apache Spark, Deep Learning, Information Technology, Data Analytics, Virtual Agents - **Published:** July 17, 2026 - **Apply:** https://www.dice.com/job-detail/1437e090-f22e-4efa-8ce6-b5efe03efc66 ## 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 backtested 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., * 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 5 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 3 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), * Master?s Degree in ?STEM? field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in ?STEM? field (Science, Technology, Engineering, or Mathematics) * At least 2 years? experience in AML modeling or related domain (e.g. Fraud, Credit Risk, etc.) * At least 1year of experience developing and evaluating production-grade GenAI, Agentic AI, and/or LLMs based systems, including experience with vector databases, LLM fine tuning, RAG, and use of LangGraph or LlamaIndex * At least 1 year of experience working with AWS * At least 3 years? experience in Python and SQL * At least 3 years? experience with machine learning ## Description The Anti-Money Laundering (AML) Modeling and Advanced Data Insights team is on a journey to modernize the way Capital One identifies potential money laundering, fraud, terrorist financing, and human trafficking through the use of advanced analytic techniques, statistics, and machine learning models. We develop predictive models, monitoring dashboards, and reporting using tools such as AWS, Snowflake, Python, and Spark. Our team produces the model outputs and data insights to operate our AML program efficiently and effectively. As the model developers for advancing transaction monitoring and customer risk rating with machine learning, our team is responsible for end to end development, deployment, and monitoring of production models., * Partner with a cross-functional team of data scientists, software engineers, business analysts, risk managers, and product owners to deliver industry-leading risk management products * Leverage a broad stack of tools and technologies ? Python, Conda, AWS, Spark, dbt, and more ? to build production-ready pipelines for data sourcing, model development, and model scoring * Build machine learning models and AI tools through all phases of development, from design through training, evaluation, validation, and implementation * Fine tune, evaluate, customize, and productionize Large Language Models (LLMs) * Flex your interpersonal skills to translate the complexity of your work into tangible business goals ## Related Videos - [How building an industry DBMS differs from building a research one](https://www.wearedevelopers.com/videos/768-how-building-an-industry-dbms-differs-from-building-a-research-one) - [Detecting Money Laundering with AI](https://www.wearedevelopers.com/videos/111-detecting-money-laundering-with-ai) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Let's Get Aggregated: Custom UDAFs in Spark ](https://www.wearedevelopers.com/videos/1649-let-s-get-aggregated-custom-udafs-in-spark) - [Beyond SQL Generation: How to Teach Agents What Your Database Actually Means](https://www.wearedevelopers.com/videos/100127-beyond-sql-generation-how-to-teach-agents-what-your-database-actually-means) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [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) - [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) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Got AI ideas but no money? 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