Data Scientist Lead - Property & Casualty Loss/Risk Modeling

United Services Automobile Association (USAA)
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Job Description

At USAA, we have an important mission: facilitating the financial security of millions of U.S. military members and their families. Not all of our employees served in our nation’s military, but we all share in the mission to give back to those who did. We’re working as one to build a great experience and make a real impact for our members.

We believe in our core values of honesty, integrity, loyalty and service. They’re what guides everything we do – from how we treat our members to how we treat each other. Come be a part of what makes us so special!

The Opportunity

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; Phoenix, AZ; Colorado Springs, CO; Plano, TX or Tampa, FL. Relocation assistance is not available for this position.

We are looking for a highly skilled Data Scientist to join the Advanced Analytics and Machine Learning Team in USAA P&C Insurance.This role will be tackling some of our most challenging analytical problems in P&C Underwriting by experimenting with data, prototyping statistical models, and deploying new data science products in operations.

Translates business problems into applied statistical, machine learning, simulation, and optimization solutions to advise actionable business insights and drive business value through automation, revenue generation, and expense and risk reduction. In collaboration with engineering partners, delivers solutions at scale, and enables customer-facing applications. Leverages database, cloud, and programming knowledge to build analytical modeling solutions using statistical and machine learning techniques. Collaborates with other data scientists to improve USAA’s tooling, growing the company’s library of internal packages and applications. Works with model risk management to validate the results and stability of models before being pushed to production at scale.

What you’ll do:

  • 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 sophisticated modeling. problems/research efforts.
  • Leads efforts to build and maintain a robust library of reusable, production-quality algorithms and supporting code, to ensure model development and research efforts are transparent and based on the highest quality data.
  • Assists team with translating business request(s) into specific analytical questions, executing analysis and/or modeling, and communicating outcomes to non-technical business colleagues with a focus on business action and recommendations.
  • Manages project portfolio milestones, risks, and impediments. Anticipates potential issues that could limit project success or implementation and escalates as needed.
  • Establishes and maintains best practices for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling best practices and model risk management standards.
  • Interacts with internal and external peers and management to maintain expertise and awareness of cutting-edge techniques. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies.
  • 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 in accordance with risk and compliance policies and procedures.

What you have:

  • 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 of experience in a predictive analytics or data analysis OR advanced degree (e.g., Master’s, PhD) in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar 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 detailed, and commented where vital to explain logic (high code transparency).
  • 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 track record 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. Demonstrated history of appropriately communicating potential issues that could limit project success or implementation.
  • Expert level experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic models, discriminant analysis, support vector machines, decision trees, forest models, etc.
  • Expert level experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc.
  • 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 (or equivalent).
  • Extensive technical skills, consulting experience, and business savvy to interface with all levels and disciplines within the organization.

What sets you apart:

  • At least 3 years of experience in Property & Casualty Loss or Risk Modeling.
  • Experience leading data science projects from idea to production.
  • Experience solving data problems with high levels of ambiguity.
  • Experience working in a collaborative environment with multiple stakeholders.
  • Experience in storytelling using data visualization methods.
  • Strong attention to detail.

The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job.

What we offer:

Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. The salary range for this position is: $158,960 - $286,130.

Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors.

Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include 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, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals.

For more details on our outstanding benefits, please visit our benefits page on

Company Info.

United Services Automobile Association (USAA)

The United Services Automobile Association (USAA) is a San Antonio-based Fortune 500 diversified financial services group of companies including a Texas Department of Insurance-regulated reciprocal inter-insurance exchange and subsidiaries offering banking, investing, and insurance to people and families who serve, or served, in the United States Armed Forces. At the end of 2020, it had more than 13 million members.

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    San Antonio, Texas, United States
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