Lead Data Science Engineer for Energy & HVAC (Hybrid)

Danfoss GmbH; United States; Hybrid; USD 104,000 - 161,000; Full time

Benefits offered by this job

13th salary

Annual bonus

Pension plans

Personal insurance

Job summary

Danfoss is seeking a Lead Engineer (m/f/d) Data Science to transform product, sensor and operational data into actionable insights supporting innovation and energy efficiency. You’ll work with business teams, engineers and data platform specialists to shape AI use cases and build a robust data foundation for future intelligent solutions.

Expect to translate engineering challenges into analytical questions, develop data‑driven models, and communicate findings to technical and business

Qualifications

• Experience in data science or applied analytics in a technical, industrial or engineering environment.
• Strong analytical and problem‑solving skills with ability to translate engineering insight into data‑driven models.
• Proficiency in Python and SQL and understanding of the ML lifecycle and cloud platforms.

Responsibilities

• Translate complex business and engineering challenges into analytical questions and data‑driven insights.
• Analyze product, sensor, device and operational data to identify patterns and opportunities for optimization.
• Shape high‑value data science and AI use cases with feature definition and validation strategies.
• Collaborate with data engineers and platform teams to improve data quality and usability.
• Contribute to semantic models and knowledge graph capabilities capturing sensor and asset relationships.
• Communicate insights clearly to stakeholders to drive practical business actions.

Skills

Python

SQL

Data analysis

Cloud platforms

Tools

Knowledge graph

Job description

Danfoss is seeking a Lead Engineer (m/f/d) Data Science to transform product, sensor and operational data into actionable insights supporting innovation and energy efficiency. You’ll work with business teams, engineers and data platform specialists to shape AI use cases and build a robust data foundation for future intelligent solutions.

Expect to translate engineering challenges into analytical questions, develop data‑driven models, and communicate findings to technical and business