Data Scientist - People Analytics

Posted 2025-04-22
Remote, USA Full-time Immediate Start

About the position

The Data Scientist - People Analytics role at Penske Corporation focuses on developing advanced tools and insights for people leaders and strategic decision-makers. This position is integral to establishing predictive analytics capabilities in areas such as employee engagement, process efficiency, retention, workforce planning, risk avoidance, and diversity and inclusion. The Data Scientist will manage multiple complex projects that have organization-wide impacts, requiring collaboration across various functional departments and stakeholders.

Responsibilities
? Identify appropriate data sources to answer business questions
,
? Extract, blend, cleanse, and organize data
,
? Automate ETL processes
,
? Visualize data
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? Identify and ameliorate outliers and missing or incomplete records in the data
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? Identify appropriate techniques and algorithms for building models
,
? Create and test models
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? Build applications and embed models
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? Collaborate with various stakeholders to identify business problems
,
? Conduct ROI analysis to determine project feasibility
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? Help build business cases for significant enterprise-wide analytics initiatives
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? Engage in best practices discussions regarding modeling activities
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? Discuss project activities and results with the team
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? Participate in discussions about the company's big data vision
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? Evaluate new technologies and determine their applicability to business trends in the logistics industry

Requirements
? Master's Degree in Engineering, Operations Research, Statistics, Applied Math, Computer Science, or related quantitative field
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? PhD preferred
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? Minimum of 2+ years experience in a related field
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? 2 years experience designing and building machine learning applications using structured or unstructured datasets
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? Practical experience programming using Python, R, or other high-level scripting languages
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? Demonstrated experience with machine learning techniques including logistic regression, decision trees, random forests, and clustering
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? Knowledge and experience with SQL preferred
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? Intermediate experience in machine learning, statistical modeling, supervised/unsupervised learning, and statistical computing packages

Nice-to-haves
? Experience with advanced machine learning techniques
,
? Familiarity with big data technologies
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? Experience in the logistics industry

Benefits
? Health insurance
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? 401k retirement plan
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? Paid time off
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? Professional development opportunities

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