Senior Decision Science Analyst - P&C Claims GenAI

USAA•Tampa, FL

1d•$114,080 - $218,030•Hybrid

About The Position

We are seeking a skilled Senior Decision Science Analyst to join our team in a role that encompasses several critical areas of expertise. This individual will be responsible for AI Decision Evaluation & Optimization, ensuring that GenAI-generated recommendations are assessed, validated, and enhanced to drive superior business outcomes and decision quality. A strong background in Experimentation & Causal Analytics is essential, with a proven ability in A/B testing, causal inference, and impact measurement to quantify the true business value of GenAI solutions and differentiate correlation from causation. Furthermore, proficiency in Unstructured Data & NLP Analytics will be vital for extracting insights from diverse text-based data sources such as claims notes and documents, utilizing NLP and semantic analysis techniques. The role also demands a commitment to Responsible AI & Governance, including a solid understanding of AI risks, bias detection, explainability, compliance, and governance to ensure AI-assisted decisions are trustworthy and auditable. Finally, the candidate must possess strong Business Translation & Decision Intelligence capabilities, enabling them to translate complex business problems into AI-driven decision strategies, define key success metrics, and integrate GenAI seamlessly into operational workflows.

Requirements

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

AI Decision Evaluation & Optimization – Ability to assess, validate, and improve GenAI-generated recommendations, ensuring they drive better business outcomes and decision quality.
Experimentation & Causal Analytics – Expertise in A/B testing, causal inference, and impact measurement to quantify the value of GenAI solutions and separate true business impact from correlation.
Unstructured Data & NLP Analytics – Ability to derive insights from claims notes, documents, communications, and other text-based data using NLP and semantic analysis techniques.
Responsible AI & Governance – Knowledge of AI risks, bias detection, explainability, compliance, and governance to ensure AI-assisted decisions are trustworthy and auditable.
Business Translation & Decision Intelligence – Ability to translate business problems into AI-enabled decision strategies, define success metrics, and embed GenAI into operational claims workflows.
US military experience gained through military service or gained as 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.