Senior Manager, Data Analysis - Anti Laundering

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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 relational databases, 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.

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. Our team develops data sourcing, predictive models, monitoring, and reporting using tools such as AWS, Snowflake, Python, and Spark. As the model development team for advancing transaction monitoring with machine learning, our team is responsible for end‑to‑end development, deployment, and monitoring of these critical risk‑management models.

Our mission is to empower data‑driven decision‑making, foster innovation without limits, and make Capital One’s AML program pre‑eminent. We achieve this by implementing rigorous data governance practices, constructing analytical data stores, and harnessing the power of analytics to unlock valuable insights.

As a Senior Manager, you will partner cross‑functionally with teams throughout the enterprise including Product and Tech to deliver tangible business value. You will enhance your technical and analytical skills, while also working with leaders to influence business strategies.

On any given day you will be challenged on three types of work – Innovation, Business Intelligence and Data Management:

• Use Open Source/Digital technologies to mine complex, voluminous, and different varieties of data sources and platforms
• Build well‑managed data products, 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

• Partner with the business and translate changes to design and develop tools and techniques that enable capturing the risky behavior
• Drive analysis that provides meaningful insights on business strategies

• 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

An ideal candidate will possess strong problem‑solving and conceptual thinking abilities in addition to communication, interpersonal, and leadership skills.

• Currently has, or is in the process of obtaining, a Bachelor’s Degree in a quantitative field (e.g. Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science or a related quantitative field) plus at least 7 years of experience performing data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus at least 5 years of experience performing data analytics with an expectation that the required degree will be obtained on or before the scheduled start date.
• At least 5 years of experience performing professional data analysis work
• At least 5 years of experience leading and developing with open source data technologies
• At least 2 years of experience managing people

• Master’s Degree or PhD in a Finance, Economics, Statistics, Mathematics, Industrial Engineering, Operations Research, or a related field
• At least 7 years of experience in statistical or econometrics hands‑on work
• At least 5 years of experience manipulating and performing analysis with large data sets, including scripting experience in Python, SQL, and Spark.
• At least 5 years of…