Principal Data Scientist - AI/ML

Zobility; Oshkosh (WI); On-site; USD 180,000 - 280,000; Full time

Job summary

Zobility is seeking a Principal Data Scientist to shape the technical roadmap for enterprise AI/ML initiatives and work with executives to identify high-value analytics opportunities. You will lead end-to-end design, development, and deployment of predictive, prescriptive, and generative models.

You will mentor senior engineers and collaborate with data engineering, cloud, and software teams to ensure robust deployment, monitoring, and ROI communication to stakeholders.

Qualifications

• 8+ years of experience in analytics and AI in any business organization.
• Advanced proficiency in Python and SQL; experience with R, Scala, or C++ is a plus.
• Experience with industrial IoT, time-series sensor data, or CV/robotics domains.
• Strong ability to translate business challenges into production-ready data science solutions.

Responsibilities

• Define the technical roadmap and architecture for enterprise AI/ML initiatives.
• Partner with executive leaders to identify high-value analytics opportunities.
• Lead end-to-end design, development, and deployment of predictive, prescriptive, and generative models.
• Mentor data scientists and ML engineers across seniority levels.
• Collaborate with data engineering, cloud, and software teams for deployment and monitoring.

Skills

Python

SQL

Big Data

MLOps

CI/CD

Deep Learning

Cloud (Azure/AWS)

Education

Bachelor's degree in data science / related field

MBA

PhD

Tools

PyTorch

TensorFlow

Scikit-learn

Hugging Face

Apache Spark

Databricks

MLflow

Job description

• Define the technical roadmap and architecture for enterprise AI/ML initiatives aligned with business objectives.
• Partner with executive leaders across Access, Defense, Fire & Emergency, and Commercial segments to identify high-value analytics opportunities.
• Champion best practices for MLOps, model governance, ethical AI, and scalable data products.
• Lead the end-to-end design, development, and deployment of complex predictive, prescriptive, and generative AI models.
• Translate complex business challenges into production-ready data science frameworks
• Provide technical mentorship and guidance to senior, mid-level, and associate data scientists and machine learning engineers.
• Collaborate closely with data engineering, cloud infrastructure, and software teams to ensure robust model deployment and monitoring.
• Communicate complex analytical concepts and ROI metrics clearly to technical and non-technical stakeholders.

Requirements

• Experience with industrial IoT, telematics, edge AI, or time-series sensor data from heavy machinery, automotive, or aerospace domains.
• Background in computer vision (CV), autonomous vehicle tech, or robotics.
• 8+ years of progressive levels of responsibility in analytics and AI in any business organization
• Programming: Advanced proficiency in Python and SQL; experience with R, Scala, or C++ is a plus.
• ML/AI Frameworks: Deep experience with Scikit-learn, PyTorch, TensorFlow, XGBoost, and Hugging Face.
• Big Data & Cloud: Strong hands-on experience with cloud ecosystems (Azure or AWS), Databricks, Snowflake, and Apache Spark.
• MLOps & DevOps: Demonstrated expertise in Docker, CI/CD pipelines, MLflow, model registry, monitoring, and automated retraining workflows.
• Familiarity with Agile/Scrum delivery frameworks within large enterprise environments.
• 8+ years of experience is the manager's expectation for the principal level.
• Proven experience delivering analytics or AI projects tied to business outcomes, with demonstrated impact on revenue growth or margin improvement.
• Strong business or domain expertise in manufacturing, supply chain, operations, sales, or lifecycle services. From fields such as automotive, energy, CPG, or healthcare may also fit if they bring relevant business acumen.
• Experience working between business teams and IT/analytics: engaging senior business leaders (AVP level and above), gathering requirements, translating them into technology problems, and explaining solutions back to the business.
• Strong communication, business acumen, and ability to influence, including handling challenging conversations with senior leaders.
• Demonstrated experience mentoring junior team members.

Industry Experience

• Experience working in a portfolio company with multi-business units; preferably a manufacturing company
• Bring domain expertise in Supply chain, Manufacturing or Lifecycle services
• Consulting (nice to have)

Personal Characteristics

• Exceptional problem-solving, strategic thinking, and architectural design skills.
• Strong business acumen with the ability to link algorithmic output to measurable industrial impact
• Fit with Client culture
• AI and Business savvy person who understands how businesses make money and how AI tools can help businesses solve real business problems
• Strong EQ with the demonstrated ability to relate to both data scientists and business leaders
• A strong listener with strong written, and verbal communication skills
• Change agent who can lead via inspiration and motivation, subject knowledge, and demonstrating a "roll up your sleeves" approach to working

Preferred

• Bachelor's degree in data science, mathematics, economics, statistics, engineering, or information management
• Advanced Degree (MBA and/or PhD)
• Background in computer vision (CV), autonomous vehicle tech, or robotics.
• Familiarity with Agile/Scrum delivery frameworks
• Awareness of and openness to market-based or vendor-led AI solutions - not assuming every solution must be built in-house.
• A consultative, outcome-focused approach: able to deliver a solution by building it, partnering with a vendor or consultancy, or using managed services.
• The Principal Data Scientist serves as the technical authority and strategic lead for enterprise artificial intelligence, machine learning, and advanced analytics initiatives across Client Corporation.
• In this role, you will architect cutting-edge AI solutions to optimize smart manufacturing, predictive maintenance, aftermarket parts and sales and supply chain operations.