Decision Science Analyst I (Mid-Level) – Life Company Data and Analytics

USAA•San Antonio, TX

11h•Hybrid

About The Position

Dive into the exciting world of life insurance analytics! As a Mid-Level Decision Science Analyst I in LifeCo Data & Analytics, you'll be instrumental in uncovering key insights and developing data-backed strategies for our Life Insurance leaders. You'll collaborate closely with diverse teams, translating raw data into clear, compelling recommendations that enhance business performance. This role offers a fantastic platform to expand your analytical expertise, contribute to meaningful business growth, and be a key player in protecting more members and their families. If you thrive on solving complex problems with data and enjoy working in a collaborative environment, apply today! This role 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. We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position will be based on the San Antonio, TX. or Plano, TX. campus . Relocation assistance is not available for this position.

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. (Total of 8 years of experience without bachelor’s 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 of 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
2 or more years of working experience (including internships) in a data/analytics role
3 or more years of SQL experience
Extensive experience presenting your analytical recommendations to business partners to drive action
3 or more years of Intermediate Stats
3 or more years of Python for data analysis
3 or more years of experience in data visualization

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.