Decision Science Analyst Senior – Auto Modeling

USAA•Chesapeake, VA

1d•Hybrid

About The Position

At USAA, the mission is to empower members to achieve financial security through competitive products, exceptional service, and trusted advice, aiming to be the #1 choice for the military community and their families. The company's core values are honesty, integrity, loyalty, and service. This role is for a Decision Science Analyst Senior to join the Auto Modeling team within the Underwriting and Product Analytics organization. The position is crucial for modernizing auto insurance products by integrating data, advanced analytics, and modeling insights into product and pricing decisions. The ideal candidate is highly data-literate, capable of influencing stakeholders through thoughtful analysis, strong communication, and a deep understanding of how analytics drives strategic outcomes. USAA offers a flexible work environment requiring individuals to be in the office 4 days per week. This position can be based in San Antonio, TX, Plano, TX, Charlotte, NC, Chesapeake, VA, Colorado, CO, Phoenix, AZ, or Tampa, FL, with relocation assistance available.

Requirements

Bachelor's degree in quantitative analytics field such as Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science or other quantitative discipline; OR 4 years of related experience in statistics, mathematics or quantitative analytics (in addition to the minimum years of experience required) may be substituted in lieu of degree.
6 years of data & analytics experience OR a minimum of 4 years of data & analytics experience and up to 2 years of progressive functional business relevant experience within the respective industry of responsibility (i.e.P&C, Bank, Finance, Marketing etc.) for a total of 6 years combined experience OR advanced degree in quantitative analytics field such as Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science or other quantitative discipline and 4 years of experience in data/analytics or functional business experience within the respective industry of responsibility (i.e.P&C, Bank, Finance, Marketing, etc.).
Demonstrates advanced skills in mathematical and statistical techniques and approaches used to drive fact-based decision-making.
Advanced knowledge of data analysis tools, data visualization, developing analysis queries and procedures in SQL, SAS, BI tools or other analysis software, and relevant industry data & methods and ability to connect external insights to business problems.
Experience with new and emerging data sets, and incorporation (data wrangling, data munging) into new insights.

Nice To Haves

Experience in Property & Casualty insurance, with an understanding of how analytics informs product, pricing, and underwriting decisions.
Strong data literacy with hands-on experience leveraging analytical and visualization tools (e.g., SQL, Snowflake, Sigma, Tableau, R, Python)
Proven ability to work autonomously and lead key components of complex analytical initiatives from problem definition through implementation and business adoption.
Demonstrated ability to influence stakeholders by clearly communicating analytical findings and guiding data-driven decision-making.
US military experience through military service or a military spouse/domestic partner.

Responsibilities

Leverages advanced business, analytical and technical knowledge to participate or lead discussions with cross functional teams to understand and collaborate highly complex business objectives and influence solution strategies.
Applies advanced analytical techniques to solve business problems that are typically medium to large scale with significant impact to current and/or future business strategy.
Applies innovative and scientific/quantitative analytical approaches to draw conclusions and make 'insight to action' recommendations to answer the business objective and drive the appropriate change.
Translates recommendation into communication materials to effectively present to various levels of management.
Incorporates visualization techniques to support the relevant points of the analysis and ease the understanding for less technical audiences.
Identifies and gathers the relevant and quality data sources required to fully answer and address the problem for the recommended strategy through testing or exploratory data analysis (EDA).
Integrates/transforms disparate data sources and determines the appropriate data hygiene techniques to apply.
Thoroughly documents assumptions, methodology, validation and testing to facilitate peer reviews and compliance requirements.
Understands and adopts emerging technology that can affect the application of scientific methodologies and/or quantitative analytical approaches to problem resolutions.
Succinctly delivers analysis/findings in a manner that conveys understanding, influences various levels of management, garners support for recommendations, drives business decisions, and influences business strategy.
Provides subject matter expertise in operationalizing recommendations.
Remains informed on current data and analytics trends, (Ex: Cloud, Data Mining, Python, Neural Networks, Sensor data, IoT, Streaming/NRT data).
Identifies opportunities to continue to learn in the data and analytics space, whether informal (e.g., Coursera, Udemy, Kaggle, Code Up, etc.) or formal (e.g.Certifications or advanced coursework).
Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.