At Capital One, data is at the center of everything we do. When we launched as a startup we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. About the organization: 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, terrorist financing, and human trafficking through the use of advanced analytic techniques, statistics, and machine learning models. This Model Development team is responsible for building and maintaining suspicious activity monitoring models for the Retail Bank LOB within Capital One. The DA joining this team would have a cross-functional team of analysts working alongside them in performing statistical analysis to assess this risk. You would build and test these rules based and machine learning models using Python and SQL by developing data sourcing, predictive models, monitoring, and reporting using tools such as AWS, Snowflake, Python, and Spark. As the model developer for advancing transaction monitoring, you will be working in a team that is responsible for end to end development, deployment, and monitoring of these critical risk management models. As a Data Analyst at Capital One you will leverage analytic and technical skills to innovate, build, and maintain well-managed data solutions and capabilities to tackle business problems. On any given day you will be challenged by three types of work - Innovation, Business Intelligence and Data Management: Innovation Use Open Source/Digital technologies to mine complex, voluminous, and different varieties of data sources and platforms Build well-managed data solutions, tools, and capabilities to enable self-service frameworks for data consumers Demonstrate ability to explore and quickly grasp new technologies to progress varied initiatives Business Intelligence Partner with the business to provide consultancy and translate the business needs to design and develop tools, techniques, metrics, and dashboards for insights and data visualization Drive analysis that provides meaningful insights on business strategies Data Management Drive an understanding and adherence to the principles of data quality management including metadata, lineage, and business definitions Work collaboratively with appropriate Tech teams to manage security mechanisms and data access governance Build and execute tools to monitor and report on data quality