Data Scientist Lead

$164,780 - $314,960/Yr

United Services Automobile Association (USAA) - Colorado Springs, CO

Full-time - Senior

Colorado Springs, CO

Religious, Grantmaking, Civic, Professional, and Similar Organizations

About the position

At USAA, we are seeking a dedicated Data Scientist Lead - Model Implementation. In this role, you will translate business problems into applied statistical, machine learning, simulation, and optimization solutions to inform actionable business insights and drive business value through automation, revenue generation, and expense and risk reduction. You will collaborate with engineering partners to deliver solutions at scale and enable customer-facing applications. This position requires leveraging database, cloud, and programming knowledge to build analytical modeling solutions using statistical and machine learning techniques. You will also work with model risk management to validate the results and stability of models before they are pushed to production at scale.

Responsibilities

• Gathers, interprets, and manipulates complex structured and unstructured data to enable advanced analytical solutions for the business.
• Leads and conducts advanced analytics leveraging machine learning, simulation, and optimization to deliver business insights and achieve business objectives.
• Guides team on selecting the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs.
• Develops and deploys models within the Model Development Control (MDC) and Model Risk Management (MRM) framework.
• Composes and peer reviews technical documents for knowledge persistence, risk management, and technical review audiences.
• Partners with business leaders from across the organization to proactively identify business needs and proposes/recommends analytical and modeling projects to generate business value.
• Works with business and analytics leaders to prioritize analytics and highly complex modeling problems/research efforts.
• Leads efforts to build and maintain a robust library of reusable, production-quality algorithms and supporting code.
• Assists team with translating business request(s) into specific analytical questions, executing analysis and/or modeling, and communicating outcomes to non-technical business colleagues.
• Manages project portfolio milestones, risks, and impediments.
• Establishes and maintains best practices for engaging with Data Engineering and IT to deploy production-ready analytical assets.
• Interacts with internal and external peers and management to maintain expertise and awareness of cutting-edge techniques.
• Serves as a mentor to data scientists in modeling, analytics, computer science, business acumen, and other interpersonal skills.
• Participates in enterprise-level efforts to drive the maintenance and transformation of data science technologies and culture.
• Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled.

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 may be substituted in lieu of degree.
• 8 years of experience in predictive analytics or data analysis OR Advanced Degree (e.g., Master's, PhD) in a quantitative discipline and 6 years of experience in predictive analytics or data analysis.
• 6 years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models.
• 4 years of experience in one or more dynamic scripted language (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models.
• Expert ability to write code that is easy to follow, well documented, and commented where necessary to explain logic.
• Strong experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc.
• Strong experience in working with structured, semi-structured, and unstructured data files such as delimited numeric data files, JSON/XML files, and/or text documents, images, etc.
• Excellent demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics.
• Proven ability to assess and articulate regulatory implications and expectations of distinct modeling efforts.
• Project management experience that demonstrates the ability to anticipate and appropriately manage project milestones, risks, and impediments.
• Expert level experience with the concepts and technologies associated with classical supervised modeling for prediction.
• Expert level experience with the concepts and technologies associated with unsupervised modeling.
• Demonstrated experience in guiding and mentoring junior technical staff in business interactions and model building.
• 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.
• A strong track record of communicating results, insights, and technical solutions to Senior Executive Management.

Nice-to-haves

• Expertise in Python and large-scale datasets and modern data architectures.
• Demonstrated experience developing ML/AI models and experience with ML lifecycle ML Ops tools and deployment solutions.
• Proven experience building gen AI models.
• Hands-on experience with cloud services for model development and deployment.
• US military experience through military service or a military spouse/domestic partner.

Benefits

• Comprehensive medical, dental and vision plans
• 401(k)
• Pension
• Life insurance
• Parental benefits
• Adoption assistance
• Paid time off program with paid holidays plus 16 paid volunteer hours
• Various wellness programs
• Career path planning and continuing education assistance.