Job Number: R0063316
Quantitative Data Analyst
Work as a member of an analytics team and apply expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers. Assist the client with comprehending how their data can drive their business processes, promote the growth of their programs, and support their business decisions. Analyze data and translate those into recommendations for working with various teams across the organization. Maintain responsibility for developing and delivering meaningful metrics, trends, key insights, and detailed analyses using various tools and resources, including SAS, R, Python, and Microsoft Excel. Contribute to the development of a client's programs and document processes and procedures used in the collection, management, and distribution of data. Create executive briefing presentations and visualizations and drive innovation and process improvement within the reporting and data analysis spectrum.
-Experience in conducting statistical analysis and building models with advanced scripting language, including Python, R, SPSS, or other analytic tools
-Experience with SQL
-Experience with gathering, analyzing, and interpreting large datasets
-Experience with producing interactive business intelligence dashboards or Web applications
-Experience with performing project-based analytics work in an Agile environment
-Experience in generating and communicating business insights to executive stakeholders, including storytelling with data
-Ability to display a proven track record of decision making and problem-solving based on analytics and think conceptually with excellent quantitative orientation
-Ability to learn new applications, processes, and procedures quickly and apply them in a fast-paced business environment
-Ability to obtain a security clearance
-BA or BS degree
-Experience with Big Data technologies, including HDFS, Spark, Azure Data Lake Store, or similar
-Experience as a strategic, intellectually curious thinker with a focus on outcomes
-Knowledge of statistical methods, including Bayesian Networks Inference, linear and non-linear regression, KNN, SVM, or Random Forests
-Ability to collaborate in a team environment and exercise independent judgment and initiative
-Active Secret clearance preferred
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information.
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