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 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 resolves appropriate data hygiene techniques to apply.
Thoroughly documents assumptions, methodology, validation and testing to facilitate peer reviews and compliance requirements.
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.

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 field; OR 4 years of related experience in statistics, mathematics or quantitative analytics 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 with 2 years experience in data/analytics or functional business experience within the respective industry of responsibility.
Demonstrates competency in mathematical and statistical techniques 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.

Mid-level Decision Science Analyst – Member Value

Key skills