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United States Postal Service · 5 hours ago

Data Scientist

Raleigh, NC

Full-time

Onsite

Mid, Senior Level

4+ years exp

The United States Postal Service is seeking a Senior Data Scientist to lead technology and architecture analytics projects. The role involves improving technology devices and operations through exploratory data analysis, statistical modeling, and machine learning.

Delivery ServiceEnterprise SoftwareGovernmentLogisticsPackaging ServicesTransportation

Hiring Manager

Leandra Perez

Responsibilities

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

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

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

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

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

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

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

Qualification

Data analysisStatistical modelingMachine learningSPSSSASSQLProgramming languagesCommunication skillsProject managementPresentation skills

Required

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

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

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

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

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

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

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

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