Payroll Analytics & Automation Lead

Penske Truck Leasing; Reading (Berks County); On-site; USD 85,000 - 120,000; Full time

Job summary

Penske Truck Leasing in Reading, PA is seeking a Payroll Business Intelligence Analyst to transform payroll data into actionable insights and build predictive solutions. You will collaborate with Payroll, HR, Finance, and IT to develop scalable analytics and automation that elevate payroll from a transactional function to a data-driven capability.

The role requires expertise in SQL and at least one statistical language, plus experience with machine learning and large datasets.

Qualifications

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or related field.
• Experience working with large datasets and applying analytical techniques.
• Strong programming skills in SQL and at least one statistical language (Python, R).
• Experience building and implementing machine learning or statistical models.

Responsibilities

• Analyze large-scale payroll datasets to identify trends, anomalies, and business opportunities.
• Develop dashboards and visualizations to provide actionable insights to stakeholders.
• Build predictive models (forecasting, classification, clustering) to improve payroll decisions.
• Develop data pipelines and transformation processes to support analytics and modeling.
• Automate reporting and data workflows to reduce manual effort.

Skills

Data analysis

Analytical thinking

Communication

Education

Bachelor’s or Master’s degree in Data Science/Statistics/CS

Tools

SQL

Python

R

Power Automate

Job description

Penske Truck Leasing in Reading, PA is seeking a Payroll Business Intelligence Analyst to transform payroll data into actionable insights and build predictive solutions. You will collaborate with Payroll, HR, Finance, and IT to develop scalable analytics and automation that elevate payroll from a transactional function to a data-driven capability.

The role requires expertise in SQL and at least one statistical language, plus experience with machine learning and large datasets.