Mid-Level Decision Science Analyst - P&C Underwriting Analytics

USAA•Tampa, FL

1d•$93,770 - $168,770•Hybrid

About The Position

This Decision Science role is integral to optimizing underwriting strategies within the personal lines Property & Casualty business. The role focuses on applying advanced analytics and data-driven insights to answer critical business questions and support decision-making. Working with established data assets and in close partnership with business stakeholders, this role will analyze complex datasets, synthesize findings, and translate results into clear, actionable recommendations. Insights will directly inform strategic decisions related to risk precision, risk sharing, risk mitigation, and risk acceptability, ultimately driving profitable growth and enhanced member protection. This role is remote eligible in the continental U.S. with occasional business travel. However, individuals residing within a 60-mile radius of a USAA office will be expected to work on-site four days per week.

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.
4 years of experience in data/analytics or functional business experience within the respective industry of responsibility (i.e. P&C, Bank, Finance) 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 with 2 years experience in data/analytics or functional business experience within the respective industry of responsibility (i.e. P&C, Bank, Finance).
Demonstrates competency in mathematical and statistical techniques and approaches used to drive fact-based decision-making.
Intermediate and some 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.

Nice To Haves

US military experience through military service or a military spouse/domestic partner
Deep experience with descriptive and prescriptive analytical work supporting Core P&C Insurance Functions
Extensive experience using Python for data analysis
High level of proficiency with storytelling with data/ presentation of analytical insights to non-technical audiences
Solid grasp of statistical modeling principles and the ability to interpret model outputs to derive actionable business insights.
Strong demonstration of a desire to continuously learn and refine analytical techniques and business acumen

Responsibilities

Leverages intermediate and some advanced business, analytical and technical knowledge to participate in discussions with cross functional teams to understand and collaborate on business objectives and influence solution strategies.
Applies advanced analytical techniques to solve business problems that are typically medium to large scale with 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 colleagues for peer review and mid-to-upper-level 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.
Delivers analysis/findings in a manner that conveys understanding, influences mid to upper level management, garners support for recommendations, drives business decisions, and influences business strategy.
Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.