Executive Director, Data Scientist: AML Modeling and Analytics

USAA•San Antonio, TX

1d•$224,250 - $403,650•Hybrid

About The Position

The Executive Director, Data Scientist, leads a team of AML professionals responsible for advanced analytical solutions that include predictive analytics, machine learning, simulation, and optimization techniques that support the AML and Sanctions programs, including transaction monitoring and customer risk scoring. Influences the creation and execution of operational and strategic plans by leveraging deep technical acumen and in-depth understanding of business processes and practices. Influences IT and other areas to build major improvements to analytical processes and systems. Leads the development of data science solutions and long-term goals and strategies. Maintains relationships with academic and industry thought leaders to ensure the enterprise has access to cutting-edge thinking and technologies. We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX, OR Charlotte, NC,. Relocation assistance is available for this position.

Requirements

Bachelor's degree in Computer Science, Applied Mathematics, Quantitative Economics, Statistics, or directly related field ; OR 4 years of related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree.
10 years of experience in predictive modeling, large data analysis and computer science.
4 years of people leadership experience in building, managing and/or developing high-performing applied analytics (data science, decision science, etc.) teams.
Experience in stochastic modeling, machine learning, and other advanced mathematical techniques (e.g., neural nets, simulation, graph analysis).
Extensive knowledge in at least one advanced analytics programming language (e.g., Python, R, etc.).
A strong track record of communicating results, insights, and technical solutions to Senior Executive Management (or equivalent).
Extensive experience in data mining and statistical analysis.
Demonstrated pattern recognition and predictive modeling skills.
Knowledge and application of Data Science principals and experience with data science methodologies.
Experience with the following statistical and predictive modeling approaches: Gaussian Process; Markov Models; Hierarchical Clustering; K-Means; Linear Regression; Logistic Regression; Monte Carlo Simulation; Neural Networks.
Extensive technical skills, consulting experience, and business savvy to interface with all levels and disciplines within our customers' organization.
Demonstrated experience leading business or product/portfolio transformation through use of advanced analytics.
Demonstrated ability to communicate ideas with team members and/or business leaders to convey and present very technical information to an audience that may have little or no understanding of technical concepts in data science.

Nice To Haves

Strong leadership experience
Anti-money laundering experience
Technical background, has owned AML models including transaction monitoring, customer risk scoring, and sanctions screening models
Strong working knowledge in analytical programs and languages: Python, SQL, SAS
Strong ability to successfully work collaboratively in heavily matrixed organization
Certified: CAMS desired, CFE, SAS/SQL or other program language certifications
US military experience through military service or a military spouse/domestic partner

Responsibilities

Responsible for defining and innovating machine learning capabilities that enable business to meet strategic goals.
Leverages state-of-the-art machine learning/AI tools and analytical methodologies to develop and implement various types of predictive models with the targeted goal of achieving business priorities.
Partners with key stakeholders from business units to gather, analyze, and determine data and information requirements in support of the data and analytics roadmap, and determine the feasibility of those requirements from a technical perspective.
Collaborates with other senior leaders to set the strategic direction of the business through data and information exploration, research of emerging technologies or analytical techniques and long-term defined/project specific strategic assignments.
Agility to collaborate and influence peers and customers as the Data Science discipline continues to scale and mature.
Responsible for the exploration of promising new technologies, analytical methods, and data sources (internal to USAA & external) that have potential to add value to the enterprise.
Accountable for solutions that influence decision makers and drive change by driving and helping to set the business direction, environment, and strategies.
Accountable for the design and construction of large and complex data sets from large amounts of structured and unstructured data (internal and external) to enable analytical solutions.
Builds and leads a high performing team of experts in advanced analytics; develops team reputation as highly skilled experts in the field of data science.
Strengthens data stewardship, actively manages information risk, and collaborates in division and enterprise data and analytics leadership forums to further information governance and mitigate information and business risks.
Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures