FUNCTIONAL PURPOSE:

Serves as a senior data scientist for technology and/or architecture analytics projects and/or initiatives within an assigned domain. This role will primarily support the improvement of technology devices, applications, and/or operations using exploratory data analysis processes, techniques, and tools including statistical modeling, data exploration, and machine learning. Depending upon assignment, this role will support one of the following organizations: Technology Applications, Network and Compute Technology, or Endpoint Technology.

DUTIES AND RESPONSIBILITIES:

1. Serves as a senior data scientist; leads the research, analysis, and interpretation of data for various large sized projects within an assigned domain; provides project oversight and technical guidance to others. Develops algorithms to evaluate domain data (e.g., customer, finance, operational) to address business questions or issues.

2. Provides guidance to others on statistical and computational methodologies (e.g., probability sampling, experimental design, data quality) to analyze, interpret, and display data.

3. Develops and presents background material on procedures, concepts, policy, statistical models, results, and proposed designs. Leads the development of scalable, efficient, and automated processes for data analyses and model development using programming languages.

4. Uses statistical and exploratory data analysis techniques, methods and tools to measure and track performance and identify opportunities for improvement. Interprets results and translates findings into actionable recommendations.

5. Develops recommendations for new policies, systems, procedures and training programs; coordinates procedural and technical instructions into a cohesive, operational, documentation of system operations. Coordinates the communication of new policies and procedures with employees and stakeholders.

6. Collaborates with Information and Technology related business units to coordinate the integration and implementation of new developments to applications and technologies.

7. Researches industry best practices, trends, and insights; identifies opportunities to incorporate emerging tools, techniques and methods into existing processes. Develops and implements recommendations based on findings.

REQUIREMENTS:

1. Ability to conduct data analysis and modeling sufficient to gather data, identify trends and insights, apply analytical method and techniques, and develop actionable recommendations on a project basis for technology applications and/or operations initiatives.

2. Ability to use statistical and business intelligence software packages such as SPSS, SAS, OLAP, SQL, VBA, or standard MS Office products at a level sufficient to analyze, interpret, and display complex data results.

3. Ability to use statistical and/or exploratory data analysis methods, tools, techniques sufficient to develop recommendations that summarize trends and insights.

4. Ability to use common programming languages sufficient to maintain and troubleshoot statements and queries.

5. Ability to communicate orally and in writing to provide feedback, technical guidance, and instruction to cross functional teams in the development of data science tools and processes.

6. Ability to lead projects, including organizing and coordinating the activities of project team members, and ensuring tasks are completed in a timely manner.

7. Ability to develop and present reports and presentations that summarize recommendations and explain data in a manner appropriate for technical and non-technical audiences. 8.

EDUCATION/EXPERIENCE REQUIREMENT:

Applicants must possess one of the following:

1. Bachelor's or Graduate degree in Information Technology, Data Science, or a closely related field from an accredited college or university by a national or regional accreditation organization recognized and sanctioned by the U.S. Department of Education. OR 2. Possess four (4) years of professional experience which includes facilitating Information Technology projects using data exploration techniques, machine learning, or statistical modeling.

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