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Provide decision support for business areas across the enterprise. 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.

Duties and Responsibilities:

Performs professional duties in support of operations for the functional area assigned.

Applies foundational functional knowledge to produce work deliverables in support of departmental initiatives.

Manages limited departmental projects and/or participates as a project resource on larger initiatives.

Identifies opportunities and facilitates basic improvements to processes and systems.

Performs routine tasks under direct supervision and within established procedures and guidelines.

May interact with clients for technical requests to understand requirements and limitations in different phases of project lifecycle to include research, testing and implementation


Minimum Education:

Pursuing a bachelor’s degree or higher in Data & Analytics, Economics, Finance, Statistics, Mathematics, Actuarial Sciences or other quantitative discipline at a 4-year accredited university

Graduation date cannot be prior to the end of the internship.


Minimum Work Experience:

 0 to 2 years of related experience and accountability for simple to moderately complex tasks and/or projects required.

Foundational and conceptual knowledge of the function/discipline and demonstrated application of knowledge, skills and abilities towards work products required.

Foundational level of business acumen in the areas of the business operations, industry practices and emerging trends required.


Preferred Education:

Pursuing a Master's degree in Data & Analytics, Economics, Finance, Statistics, Mathematics, Actuarial Sciences or other quantitative discipline at an accredited university

Preferred Work Experience:

Experience with one or more of the following: Python, SAS, SAS Enterprise Guide, SAS Enterprise Miner, R, Jupyter Notebok, Spark, Hadoop, HDP, Hive, Beeline, Pig, Command Line, Linux, Unix, Tableau, SPSS, SPSS Modeler, MATLAB

Experience with Data Mining, Data Cleaning, Statistical Modeling, Sampling, Text Analysis, Machine Learning, Dashboards, Visualization