Decision Science Analyst Senior – Life Company Data and Analytics - Paid Media Performance Analyst – Social & Search

USAA•San Antonio, NC

3d•Hybrid

About The Position

USAA Life Company is looking to build on its foundation of exceptional service to grow and serve more members. This role will play a critical part in that growth by delivering actionable insights and optimization recommendations across Paid Social, Paid Search, and emerging AI-powered search experiences. The ideal candidate combines strong SQL and Python skills with hands-on experience analyzing paid media performance, audience segmentation, and conducting incrementality testing that improve engagement and acquisition. This individual will leverage advanced analytics, data visualization, and storytelling to connect marketing investments to business outcomes while partnering closely with the channel managers, product marketers, and campaign analysts to drive measurable growth. This role provides decision support for business areas across the association. This will be responsible for applying mathematical and statistical techniques and/or innovative /quantitative analytical approaches to draw conclusions and make 'insight to action' recommendations to answer business objectives and drive change. The essence of work performed by the Decision Science Analyst involves gathering, manipulating and synthesizing data (e.g., attributes, transactions, behaviors, etc.), models and other relevant information to draw conclusions and make recommendations resulting in implementable strategies.

Requirements

Bachelor's degree in Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science, or a business or quantitative field OR 4 years of relevant education and/or experience (in addition to the minimum years of experience required) may be substituted in lieu of degree. (Total of 10 years of experience without bachelor’s 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. Life Insurance, 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. Life Insurance, 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

US military experience through military service or a military spouse/domestic partner .
5+ years of experience using SQL and Python to analyze data, develop insights, and support marketing decision-making.
3+ years of experience optimizing paid social campaigns through audience targeting, bidding strategies, budget management, retargeting, and performance analysis.
3+ years of experience optimizing paid search campaigns through keyword strategy, query analysis, bidding, and customer acquisition performance measurement.
Knowledge of AI-powered search and Answer Engine Optimization (AEO) , including emerging search behaviors and opportunities to improve brand visibility and consumer intent capture.
Experience with audience segmentation, creative testing, and influencer/creator performance analysis , translating insights into actionable recommendations.
Experience with experimentation and measurement , including A/B testing, incrementality studies, and control vs. test frameworks to evaluate marketing effectiveness.
Strong analytics, data visualization, and storytelling skills , with the ability to connect paid media performance to website engagement and conversion outcomes.
Familiarity with Meta Ads Manager, Adobe Analytics, Google Ads, Bing Ads, SA360, Floodlight tags, and attribution tools.

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).
Ensure risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.