Data Scientist - Machine Learning - Residential/Commercial HVAC Products

About The Job

Role & Responsibilities

• Develop Fault Detection & Diagnostic algorithms for Carrier Residential / Commercial HVAC Products.
• Identify methods to detect component level faults such as Compressor Failure / Leakage / Inverter / Outdoor Fan / Outdoor Heat exchanger/ Unit Health index.
• Algorithm development includes understanding experimental data, data cleanup, model building, model validation, model metrics evaluation.
• Work with Carrier engineering design centers globally on challenging modeling problems and promotes the application of Data Science techniques to support design decisions.
  

Education / Certifications

• Candidates must possess a MTech / MS or PhD in Mechanical, Electrical, Industrial Engineering or Physics.
• BTech with strong skills is also preferred.
  

Domain Knowledge & Skills

• Should have 8+ of Industrial experience preferably in HVAC / Automotive / Aerospace domain (having thermal background)
• Proficient in python programming
• strong background in data analytics and machine learning
• More than 3yr experience in developing data-driven classification or regression models/algorithms in HVAC and building or relevant areas.
• knowledge of vapor compression cycle, heat transfer and thermodynamics.
• Must be able to climb a learning curve quickly to become contributing within weeks and work independently with high-level direction only.
  

In Addition, The Ideal Candidate Should

• Follow Agile development process during daily work.
• Be able to work as a part of a multidisciplinary team and in a global environment (our engineers are in the US, Italy, France, Germany, China, India. We collaborate with research institutions worldwide)
• Observe discipline with the development and adoption of standard development processes.
• Have a solid track record of working under pressure and focus on results.
• Solid technical writing, presentation, and communication skills.