Senior Data Scientist: AI/ML & Data Engineering Lead

Penske; Reading (Berks County); On-site; USD 120,000 - 180,000; Full time

Job summary

Penske is seeking a Senior Data Scientist in Reading, PA to transform complex data into business value using AI/ML, build scalable analytics and production-ready capabilities, and lead data-driven decision making across the organization.

You will mentor junior data scientists, collaborate with cross-functional teams, and guide multiple medium- to large-scale projects from concept to implementation, delivering measurable outcomes.

Qualifications

• Bachelor's degree in Engineering, Data Science, Computer Science, Statistics, Mathematics, or related field.
• Minimum 6 years of experience designing and building data science, machine learning, or AI applications using structured or unstructured datasets is required.
• Experience using programming and statistical tools (e.g., Python, R, SQL, Dataiku, AWS, Oracle or similar) to manipulate data and generate insights from large datasets is required.
• Demonstrated experience with multiple machine learning techniques, such as logistic regression, decision trees, random forests, clustering, and other predictive modeling methods is required.
• Experience working with cloud platforms and data environments, such as AWS and Oracle, is preferred.
• Experience applying AI techniques, including generative AI, large language models (LLMs), natural language processing, or other AI technologies, is preferred.
• Demonstrated ability to evaluate AI and machine learning solutions from a systems perspective and apply systems thinking.
• Ability to effectively prioritize and manage multiple projects simultaneously.
• Regular, predictable, and full attendance is an essential function of the job.

Responsibilities

• Identify source data and build data models to solve complex business problems.
• Extract, transform, and prepare structured and unstructured data.
• Collaborate with IT to build scalable data pipelines and analytical datasets for modeling and analytics.
• Clean, validate, and monitor data quality.
• Perform feature engineering and exploratory data analysis.
• Develop data quality metrics and visualizations to identify trends and opportunities.
• Design, develop, deploy, and monitor statistical and machine learning models.
• Select appropriate statistical methods, modeling techniques, and algorithms.
• Design and evaluate predictive analytics solutions.
• Conduct statistical analyses and experiments to validate hypotheses and support business decisions.
• Develop prototypes and proof of concepts.
• Operationalize analytical solutions for production use.
• Support the AI/ML lifecycle by monitoring model performance and driving continuous improvement.
• Monitor model performance, address model drift, and improve business outcomes.
• Apply advanced analytical techniques, including forecasting, classification, clustering, and NLP, and Sentiment Analysis.
• Apply AI techniques, including generative AI, agentic AI, and large language models (LLMs), where appropriate to enhance analytical solutions.
• Lead multiple medium- to large-scale data science initiatives from concept through implementation.
• Translate business challenges into analytical solutions.
• Define technical approaches and project methodologies.
• Establish best practices for data science development, documentation, and model governance.
• Partner with Enterprise Engineering, Advanced Analytics, HRIT, and other cross-functional teams to deliver enterprise solutions.
• Mentor and provide technical guidance to junior data scientists.
• Evaluate emerging technologies and recommend improvements to analytical solutions and data science practices.
• Partner with business leaders and subject matter experts to identify data-driven opportunities.
• Communicate analytical methods, insights, and recommendations to technical and non-technical audiences.
• Present findings through effective data storytelling and visualization.
• Measure and communicate the business impact of analytical solutions using appropriate performance metrics.
• Create clear technical documentation and project deliverables.
• Facilitate discovery sessions and support solution design.
• Stay current with advances in data science, machine learning, AI, and cloud technologies.
• Build expertise in business domains and enterprise data assets.
• Promote responsible AI through fairness, transparency, and explainability.
• Share knowledge and best practices across the data science community.
• Identify opportunities to improve analytical capabilities and business outcomes.
• Other projects and tasks as assigned.

Skills

Python

R

SQL

NLP

Forecasting

Data storytelling

Education

Bachelor's degree in Engineering, Data Science, Computer Science, Statistics, Mathematics or related field

Tools

Dataiku

AWS

Oracle

Job description

Penske is seeking a Senior Data Scientist in Reading, PA to transform complex data into business value using AI/ML, build scalable analytics and production-ready capabilities, and lead data-driven decision making across the organization.

You will mentor junior data scientists, collaborate with cross-functional teams, and guide multiple medium- to large-scale projects from concept to implementation, delivering measurable outcomes.