Principal Engineer - Data Analytics IV

Core requirements

• 8+ years of experience is the manager's expectation for the principal level.
• Proven experience deliveringanalytics or AI projects tied to business outcomes, with demonstrated impact onrevenue growth or margin improvement.
• Strong business or domain expertise inmanufacturing, supply chain, operations, sales, or lifecycle services. Candidates from fields such as automotive, energy, Client, 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.
• Strongcommunication, business acumen, and ability to influence, including handling challenging conversations with senior leaders.
• Demonstrated experiencementoring junior team members.

Preferred

• Awareness of and openness tomarket-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.

YOUR IMPACT

• 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.

QUALIFICATIONS

• 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.

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

• 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 Qualifications

• 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