Senior Manager, Data Analysis - Anti-Money Laundering Modeling and Advanced Data Insights

Senior Manager, Data Analysis - Anti-Money Laundering Modeling and Advanced Data Insights

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.

 

As a Senior Manager, you will partner cross-functionally with teams throughout the company to validate business impacting analytical tools. You will enhance your technical and analytical skills, while also working with leaders to influence business strategies. With a network of hundreds of Data Analysts, Quants, and Data Scientists, challenging projects with an eye on the bottom line and a focus on work/life balance, we’ve created a dynamic environment with plenty of room for you to learn, grow, and realize your full potential. 

Team 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 developer for advancing transaction monitoring with machine learning, our team is responsible for end to end development, deployment, and monitoring of production models.

Role Description

On a given day you will be: 

• Planning and executing the data strategy for large scale predictive models

• Identifying technical issues in analytical tools and assessing tools risks and opportunities

• Adhering to enterprise data management practices

• Creating a long-term vision that aligns future data needs with strategic business priorities and customer needs

• Independently researching, identifying, and prototyping industry best practices for emerging analytical tools 

• Communicating results clearly and concisely both verbally and through written communications via validation reports and presentations 

• Coaching, mentoring, and supervising junior staff 

 

An ideal candidate will possess strong problem solving and conceptual thinking abilities in addition to communication, interpersonal and leadership skills. This position will be in a fast-paced and entrepreneurial environment where you will be handling multiple concurrent projects while working independently and in teams. 

 

Basic Qualifications: 

• Currently has, or is in the process of obtaining a Bachelor's Degree plus at least 7 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus at least 5 years of experience in data analytics, or currently has, or is in the process of obtaining a PhD plus at least 2 years of experience in data analytics with an expectation that required degree will be obtained on or before the scheduled start date.

• At least 5 years of experience with professional data analysis work experience  

• At least 2 years leading and developing with open source data technologies 

• At least 2 years of experience in people management

 

Preferred Qualifications: 

• Master’s Degree or PhD in a Finance, Economics, Statistics, Mathematics, Industrial Engineering, Operations Research, or a related field 

• At least 5 years of experience manipulating and performing analysis with large data sets 

• At least 5 years of experience in financial services industry 

• At least 5 years of experience in developing statistical or econometric models 

• At least 5 years of experience in validating statistical or econometric models 

• At least 2 years of experience with data governance 

• At least 2 years of experience with predictive analytics