Lead Engineer (m/f/d) Data Science
Lead Data Science Engineer at Danfoss Climate Solutions, turning product, sensor and operational data into insights and AI use cases for energy efficiency and smarter heating/cooling products. Core stack includes Python, SQL, cloud/ML platforms, semantic models and knowledge graphs.
- Compensation
- Not disclosed
- Location
- Copenhagen, DK, Hamburg, DE
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Contract
- Experience
- Not specified
- Category
- Data science
- Posted
Skills
Must have
- Strong foundation in thermodynamics and physics, with first-principles reasoning applied to heating and cooling systems
- Experience in data science, applied analytics or similar roles within a technical, industrial or engineering environment
- Strong analytical and problem-solving skills, with proficiency in Python and SQL
- Good understanding of modern data and ML environments, including cloud platforms and the ML lifecycle
- Strong communication and collaboration skills across engineering, data and business teams
Nice to have
- Experience with HVAC, refrigeration, heating/cooling, energy systems or industrial operational data
Full description
The Impact You'll Make
Do you enjoy turning complex technical data into insights that drive better products and smarter decisions? Are you passionate about combining data science with engineering and domain expertise to solve real-world challenges? Then this could be the opportunity for you.
As our Lead Engineer, Data Science, you’ll play a key role in transforming product, sensor and operational data into meaningful insights that support innovation, energy efficiency and data-driven decision-making across Danfoss Climate Solutions.
Working closely with business teams, engineers and data platform specialists, you’ll combine strong analytical capabilities with engineering and domain knowledge to identify high-value opportunities, shape AI and analytics use cases and help build a robust, AI-ready data foundation for future intelligent solutions.
What You’ll Be Doing
- Translate complex business and engineering challenges into analytical questions, data-driven models and actionable insights
- Analyze product, sensor, device and operational data to identify patterns, trends and opportunities for performance and energy optimization
- Apply engineering and domain knowledge to shape high-value data science and AI use cases, including feature definition, hypothesis development and validation strategies
- Collaborate with data engineers and platform teams to improve data quality, accessibility and usability across analytics and data products
- Contribute to semantic models and knowledge graph capabilities that capture relationships between sensors, devices, assets and their operational context
- Communicate insights and recommendations clearly to technical and business stakeholders, helping turn analytical findings into practical business actions
What We're Looking For
- Strong foundation in thermodynamics and physics, with the ability to apply first-principles reasoning to heating and cooling systems and processes
- Experience in data science, applied analytics or similar roles within a technical, industrial or engineering environment
- Strong analytical and problem-solving skills, with proficiency in Python and SQL and the ability to translate engineering insight into data-driven models
- Good understanding of modern data and ML environments, including cloud platforms and the machine learning lifecycle
- Strong communication and collaboration skills, with the ability to work effectively across engineering, data and business teams
- Experience with HVAC, refrigeration, heating/cooling, energy systems or industrial operational data is considered a strong advantage