Data Scientist

Penske•Cumru Township, PA

8d•Onsite

About The Position

Supports Penske’s Procurement & Fleet Planning team by developing and delivering advanced analytics, reporting, and data science solutions that support fleet planning, vehicle acquisition, replacement planning, lifecycle analysis, procurement strategy, supplier performance, residual value analysis, and operational efficiency. The incumbent will be responsible for converting raw data from multiple sources into actionable business intelligence through data evaluation, ETL development, dashboarding, predictive modeling, forecasting, optimization, and process improvement analysis. This role requires strong business judgment, technical analytical skills, and the ability to translate complex data findings into practical recommendations for business stakeholders. The position will support cross-functional initiatives and collaborate with internal customers, vendors, suppliers, OEMs, and business partners. This position is located at our Corporate offices in a beautiful country setting 7 miles South of Reading, PA which is a convenient commute with ample free and easy parking. The role is an in-office position where the Data Scientist is expected to be in the office full-time.

Requirements

Strong business judgment
Technical analytical skills
Ability to translate complex data findings into practical recommendations for business stakeholders
Experience with quantitative and qualitative analysis using traditional and advanced techniques, including trending, correlation, forecasting, optimization, clustering, and what-if analysis
Experience analyzing vehicle, supplier, cost, market, maintenance, telematics, resale, and operational data
Experience identifying data sources, extracting and combining data from internal and external systems, and cleansing, validating, and organizing data for analysis
Experience building and maintaining ETL processes, analytical datasets, reporting tables, and repeatable workflows
Experience designing, testing, validating, and refining predictive, forecasting, optimization, and machine learning models
Experience building dashboards, reports, visualizations, and analytical tools
Experience partnering with stakeholders to define business problems, project scope, data availability, expected outcomes, and practical analytical solutions
Experience collaborating with internal teams, vendors, suppliers, OEMs, and cross-functional partners
Experience maintaining documentation, data definitions, assumptions, model logic, reporting logic, and analytical processes
Ability to stay current on data science, analytics, automation, transportation, logistics, fleet planning, and emerging technologies
Ability to evaluate tools for business use
Ability to manage multiple tasks while supporting 1–3 simultaneous projects and meeting deadlines

Responsibilities

Perform quantitative and qualitative analysis using traditional and advanced techniques, including trending, correlation, forecasting, optimization, clustering, and what-if analysis, to support Procurement, Fleet Planning, field, and leadership teams.
Analyze vehicle, supplier, cost, market, maintenance, telematics, resale, and operational data to identify planning opportunities, cost savings, and process improvements.
Identify data sources, extract and combine data from internal and external systems, and cleanse, validate, and organize data for analysis.
Build and maintain ETL processes, analytical datasets, reporting tables, and repeatable workflows to improve data reliability and efficiency.
Design, test, validate, and refine predictive, forecasting, optimization, and machine learning models for fleet lifecycle planning, replacement planning, procurement, residual value analysis, and operational improvement.
Build dashboards, reports, visualizations, and analytical tools to communicate findings, trends, risks, and opportunities to technical and business audiences.
Partner with stakeholders to define business problems, project scope, data availability, expected outcomes, and practical analytical solutions.
Collaborate with internal teams, vendors, suppliers, OEMs, and cross-functional partners to support delivery, adoption, and rollout of models, reports, and analytics tools.
Maintain documentation, data definitions, assumptions, model logic, reporting logic, and analytical processes for reference.
Stay current on data science, analytics, automation, transportation, logistics, fleet planning, and emerging technologies; evaluate tools for business use.
Manage multiple tasks while supporting 1–3 simultaneous projects and meeting deadlines.
Other projects and tasks as assigned.