Director of Anti Money Laundering Modeling and Data Science

Key Skills

AWS, Data Analysis, Data Modeling, Database, Deep Learning, Java Programming, Large scale data processing, Machine learning techniques, Python Programming, R Programming, Risk Analytics, Scala Programming, SQL

Job Description

In Capital One’s Anti Money Laundering Modeling and Analytics Office, we defend the company against model failures and find new ways of making better decisions with models. We use our statistics, software engineering, and business expertise to drive the best outcomes in both Risk Management and the Enterprise. We understand that we can’t prepare for tomorrow by focusing on today, so we invest in the future: investing in new skills, building better tools, and maintaining a network of trusted partners. We learn from past mistakes, and develop increasingly powerful techniques to avoid their repetition. As a Director of AML Modeling and Data Science, on any given day you’ll be:

• Identifying, assessing and quantifying the risks stemming from financial crime related activity within the bank through the design of effective models and controls of detecting such outlying behavioral patterns. You will also be a leader in determining the next evolution of the current models in use and future roadmap
• Familiarity in implementing, testing, or developing AML surveillance models for use in Retail, Small Business and Commercial and Lending Lines of Business 
• Consistent record of strong quantitative testing and statistical analysis techniques as it pertains to BSA/AML models, including name similarity matching, classification accuracy testing, unsupervised/supervised machine learning, network analysis, text mining, fuzzy logic matching, decision trees, etc.
• Thorough understanding of an effective financial crimes risk management framework
• Demonstrated ability to run multiple projects simultaneously
• Mature managerial skills vital to successfully administer core support and critical regulatory relationship function within a diverse organization and effectively coordinate between multiple businesses and support units; as well as the ability to autonomously and initiate, and prioritize the portfolio of work for your team
• The ability to interact effectively at all levels of the organization, including stakeholders internal and external to AML Compliance
• The ability to identify, analyze, and interpret trends or patterns in extremely large complex data sets
• Organize data management output, including continual process improvements and documentation
• Communicate analytical insights clearly and concisely to individuals from diverse backgrounds up and down the organization
• Assessing, challenging, and at times defending state-of-the-art decision-making systems to internal and regulatory partners; distilling disparate details of complex interconnected systems into concrete actions with clear business value 
• Overseeing development of benchmark and challenger models to stress test critical modeling decisions
• Developing new ways of identifying weak spots in model predictions earlier and with more confidence than the best available methods
• Experience working on Transaction Monitoring product implementations, such as Actimize and Mantas; preferably modern transaction monitoring systems leveraging machine learning algorithms for detection

Role Description
 

In this role, you will:

• Lead a cross-functional team of data scientists, risk managers, and product managers to manage the risk and uncertainty inherent in statistical models in order to lead Capital One to the best decisions, not just avoid the worst ones.
• Leverage open source programming languages and technologies to support a wide range of large scale modeling efforts
• Build and validate machine learning models through all phases of development, from design through training, evaluation, and implementation
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals, and challenge model developers to advance their modeling, data, and analytic capabilities
• Have both knowledge of and experience with the latest AML transaction monitoring technology trends
• Enthusiastic about collaborating with internal centers of excellence in the development of cutting edge AI tools and technology (e.g. deep learning, CNN, etc.)
   

?The Ideal Candidate is:

• 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.
• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.
• 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.

?A successful Candidate will have: 

• Experience setting and implementing broad strategic vision for ML applications, underlying platforms, and software 
• Demonstrated technical open source community involvement through software contributions, posters, presentations, and other participation. Expertise in testing of machine learning and statistical software. Experience with open source software packages, environment management, reproducibility, and governance
• High motivation, adaptability and being collaborative. An individual who can handle ambiguity and enjoys building. Moving in a fast-paced environment excites you and are looking for an opportunity to be a member of an innovative compliance team that will be building and implementing solutions until any other AML team in banking
   

Basic Qualifications:

• Bachelor’s Degree plus 9 years of experience in data analytics, or Master’s Degree plus 7 years of experience in data analytics, or PhD plus 4 years of experience in data analytics
• At least 4 years of experience in open source programming languages for large scale data analysis
• At least 4 years of experience with machine learning
• At least 4 years of experience with relational databases

Preferred Qualifications:

• PhD in -STEM- field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics
• At least 1 year of experience working with AWS
• At least 3 years of experience managing people
• At least 5 years of experience in Python, Scala, or R for large scale data analysis
• At least 5 years of experience with machine learning
• At least 4 years of experience with AML or other financial crime related area
• At least 3 years of experience in managing a large technical team
• At least 3 year of experience in defending regulatory models both internally and externally

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

No agencies please. Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.