Director Data Scientist – Bank AI/ML – Model Development
| Company | USAA |
|---|---|
| Location | Tampa, FL, USA, Colorado Springs, CO, USA, Plano, TX, USA, Charlotte, NC, USA, San Antonio, TX, USA, Phoenix, AZ, USA |
| Salary | $189370 – $361950 |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s, PhD |
| Experience Level | Senior, Expert or higher |
Requirements
- Bachelor’s degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline; OR 4 years of experience in statistics, mathematics, quantitative analytics, or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree.
- 8 years in predictive modeling, model governance, machine learning and large data analysis., OR Advanced Degree (e.g., Master’s, PhD) in Mathematics, Statistics, Data Science, Computer Science, or related quantitative STEM field (Science, Technology, Engineering and Math) field and 6 years in predictive modeling, model governance, machine learning and large data analysis.
- 3 years of direct management experience.
- Strong communication skills; demonstrated ability to interpret and translate complex technical information to diverse audiences.
- Experience with various languages, applications, and technologies (such as SQL, Python, R, Spark, Hadoop etc.) commonly associated with delivery of Data Science solutions.
- Experience in developing and reviewing modeling solutions based on broad range of techniques – e.g., linear and logistic regressions, time series methods, survival analysis, support vector machines, neural networks, decision trees, random forests, gradient-boosting methods, deep learning, k-means and other clustering methods, simulation methods, or other advanced techniques.
- Demonstrated ability to apply best practices in modeling and machine learning techniques to solve business problems.
- Demonstrated ability to write and review complex technical documentation, communicate modeling insights and technical details to business leaders, technical and non-technical audiences.
- A strong track record of communicating results, insights, and technical solutions to Senior Executive Management (or equivalent).
- Deep technical skills, consulting experience, and business savvy to interface with all levels and disciplines within the organization.
Responsibilities
- Acts as advanced analytics thought leader and advisor to the business to shape strategies that drive competitiveness and differentiation.
- Influences business, data, and technology leaders to invest, sustain and expand advanced analytical capabilities by actively participating in strategy, planning, and budgeting exercises.
- Leads and develops team to build and deploy various advanced analytical solutions in an agile and collaborative environment across business, data, and technology organizations. Enables team’s success by simplifying processes across the model development lifecycle and driving automation.
- Identifies, scopes, and manages complex analytical projects in collaboration with business stakeholders, often translating results to non-technical business executives.
- Champions and manages efforts to deliver business insights via scalable, automated solutions using machine learning, simulation, and optimization.
- Responsible for ensuring all modeling and machine learning solutions adhere to industry standards, model risk policy, and regulatory expectations.
- Partners with enterprise analytical and IT teams to build USAA core capabilities and processes.
- Identifies additional resource needs ranging from IT investments, 3rd party support or additional analysts.
- Builds and oversees a team of Data Scientists through ongoing execution of recruiting, development, retention, coaching and support, performance management, and managerial activities.
- Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.
Preferred Qualifications
- Demonstrated leadership across diverse data science teams with a focus on delivering results in banking and financial services.
- Strong communication skills with the ability to influence stakeholders and align cross-functional teams.
- Deep understanding of model governance, regulatory expectations and best practices in AI/ML deployment.
- Proven track record of developing talent fostering collaboration and driving strategic data science initiative across the organization.