Decision Science Analyst Senior

USAA•Tampa, FL

1d•$114,080 - $218,030•Hybrid

About The Position

Member Demand Generation Marketing is fundamental to deepening member relationships with USAA. This role will significantly enhance our analytical expertise in Member Demand Generation Marketing, enabling data-driven optimizations that accelerate business performance across the entire member lifecycle. The ideal candidate will possess a strong understanding of member journeys and the effectiveness of various marketing channels in nurturing and retaining members. As a dedicated Decision Science Analyst Senior, you will Provide decision support for business areas across the association. Staff in this area 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 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 analyzing and optimizing Demand Generation tactics throughout the lifecycle of a Membership e.g., Segmentation, Propensity Modelling, Triggers, Behaviors, Demographics, Lifecycle, Risks, Churn, Retention, Cohort Analysis
Experience analyzing and optimizing Marketing Channels to nurture Membership (e.g., Email, SMS, Direct Mail, Outbound Call), including remarketing/retargeting campaigns and next-best-action algorithms
Experience optimizing performance both within a single business unit/product, and across multiple business units/products (e.g., up-sell/cross-sell)
Expertise in designing and executing A/B tests to drive performance outcomes
Experience leading analytical workstreams and collaborating cross-functionally to drive company-wide goals
US military experience through military service or a military spouse/domestic partner

Responsibilities

Provide decision support for business areas across the association.
Apply 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.
Gather, manipulate and synthesize data (e.g., attributes, transactions, behaviors, etc.), models and other relevant information to draw conclusions and make recommendations resulting in implementable strategies.
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.