Staff Data Scientist

Penske Logistics LLC; Beachwood (OH); On-site; USD 140,000 - 190,000; Full time

Job summary

Penske Logistics LLC is seeking a Staff Data Scientist to lead enterprise-wide data science, AI, and predictive analytics initiatives from Beachwood, OH. The role combines project leadership, technical guidance, and cross-functional collaboration to deliver scalable ML solutions.

The candidate will oversee multiple high-impact projects, mentor data scientists and engineers, and drive MLOps best practices across the organization.

Qualifications

• Master's degree required; preferred concentrations in Engineering, Operations Research, Statistics, Applied Math, Computer Science, Data Science or related

Responsibilities

• Identify high-value analytics & AI opportunities with business leaders; develop ROI models to prioritize initiatives.
• Lead Data Science projects: translate requirements, select modeling techniques, and manage model lifecycle.
• Provide technical guidance on ML algorithms, experimentation, and cloud-native data engineering patterns; mentor team members.
• Manage projects: create plans, milestones, and communications for strategic initiatives; coordinate with vendors when needed.
• Lead technology change in Data Science, Analytics and AI by evaluating emerging platforms and driving adoption.

Skills

Predictive analytics

Machine learning

Generative AI

Forecasting

Vector databases

ML modeling

MLOps

ETL/ELT

Education

Master's Degree

Tools

MLOps tools

Vector databases

Cloud services

Job description

Staff Data Scientist

****

Location: Beachwood, OH

Shift: Monday - Friday 8am - 5pm (Onsite 4 days a week)

(Possible remote for the right candidate)

Position Summary

The Staff Data Scientist will be a key role in the Data Science and Analytics team tasked with providing technical leadership for the establishment of enterprise wide capabilities in data science, AI and predictive analytics. The Staff Data Scientist will typically work on 3-5 large projects concurrently that have organization-wide impact.In addition to these projects, the Staff Data Scientist will provide technical consultation, advice and training on all major on-going Data Science and Analytics projects. When required, the Staff Data Scientist will also act as a project manager where vendors, suppliers and consultants are engaged on key strategic and emerging technology initiatives.

Major Responsibilities

Identifying High Value Analytics & AI Opportunities

• Partner with business leaders to identify opportunities where predictive analytics, machine learning, or generative AI can improve productivity, reduce cost, or unlock new capabilities.
• Develop clear business cases and ROI models to prioritize initiatives and communicate value to senior leadership.

Lead Data Science Projects

• Translate complex business requirements into robust, scalable technical solutions.
• Select and implement appropriate modeling techniques, including classical ML, deep learning, generative AI, and reinforcement learning where applicable.
• Oversee the full model lifecycle: data exploration, feature engineering, model development, evaluation, deployment, monitoring, and continuous improvement.
• Ensure solutions are production ready, maintainable, and aligned with MLOps best practices.
• Drive organization wide adoption of models and AI systems through clear communication, documentation, and stakeholder engagement.

Technical Guidance & Thought Leadership

• Provide expert consultation on ML algorithms, model tuning, experimentation frameworks, and cloud native data engineering patterns.
• Mentor data scientists, ML engineers and AI engineers; support skill development in areas such as forecasting, ML modeling, generative AI, vector databases, and modern ETL/ELT workflows.
• Contribute to the development of internal standards, reusable components, and best practice guidelines.

Project Management

• Develop and maintain project plans, milestones, and communication strategies for strategic initiatives.
• Facilitate regular updates with stakeholders, executives, and cross functional partners.
• Coordinate with vendors, consultants, and technology partners when external expertise is required

Lead technology change in Data Science, Analytics and AI

• Evaluate emerging technologies including generative AI platforms, MLOps tools, cloud services, and data engineering frameworks to determine applicability and business value.
• Recommend and influence adoption of modern, flexible, and scalable technologies that support a unified enterprise data and AI platform.
• Drive experimentation and prototyping to accelerate innovation and reduce time to value.

Qualifications

• Master's Degree required; preferred concentrations in Engineering, Operations Research, Statistics, Applied Math, Computer Science, Data Science or related