Decision Science Analyst – Experience Forecasting


Brief Summary

                            Decision Science Analyst – Experience Forecasting

Job Role:
Applies a logical, systematic approach to problem solving using mathematical and statistical techniques and/or innovative/quantitative analytical approaches to draw conclusions and make 'insight to action' recommendations to resolve business problems 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, forecasting, and other relevant information to draw conclusions and make recommendations resulting in implementable strategies. The analysts performing decision science work may or may not perform all of the tasks described above, but will generally perform most of the tasks as part of their work. As a result of the focus on data gathering, synthesis and analysis, the work efforts will be central to fact-based decision-making.

Minimum Requirements:
•	Bachelor’s Degree in a quantitative discipline.
•	4+ years experience in a decision support analytic function.
•	4+ Quantitative analysis experience
•	Experience applying statistical/mathematical decisioning and/or testing methodologies to include multivariate regression.
•	Some experience in influencing business decisions.
•	Demonstrates competency in mathematical and statistical techniques and approaches used to drive fact-based decision-making.
•	Experience presenting and communicating findings/recommendations to team members.
•	Advanced knowledge of data analysis tools.
•	Advanced knowledge in developing analysis queries and procedures in SQL and SAS.
•	Advanced knowledge of relevant industry data & methods and demonstrated ability to connect external insights to business problems.
Preferred Requirements:
•	6+ years experience in a decision support analytic function.
•	6+ years quantitative analysis experience
•	1+ years survey science experience
•	Some experience with statistical process control, six sigma, design of experiment, AB testing, and data mining
•	R and/or Python experience
•	Experience working with large "Big Data" datasets.

Job Duties:
•	Leverages advanced business/survey/analytical knowledge to participate in and may lead discussions with cross-functional teams to understand complex business objectives and influence solution strategies. The business problems analyzed are typically medium to large scale with significant impact to current and/or future business strategy. Organizes and may oversee the development of requirements/resources necessary to meet objectives.
•	Collaborates with stakeholders to gather, consolidate and validate business assumptions relevant to member sentiment forecasting, prior to initiating and throughout the analytical process.
•	Identifies and gathers the relevant and quality data sources required to fully answer and address the problem for the recommended strategy. Integrates/transforms disparate data sources and applies the appropriate data hygiene techniques.
•	Determines and conducts appropriate exploratory data analysis (EDA) techniques on survey & operational data sets. Uses appropriate sampling techniques to select data subset for EDA.
•	Thoroughly documents assumptions, methodology, validation and testing to meet audit requirements. Subsequent analysts should be able to rely on documentation to replicate and continue work.
•	Continuously leverages expert business/survey/analytical knowledge to communicate insights with relevant cross-functional teams in order to understand the larger the potential impact the broader membership.
•	Applies innovative and scientific/quantitative analytical approaches to draw conclusions and make 'insight to action' recommendations to answer the business questions 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.
•	Succinctly delivers analysis/findings in a manner that conveys understanding, influences senior executives, and garners support for recommendations. Recommendations may have a major impact on business results. Provides subject matter expertise in operationalizing recommendations.