Honeywell Forge and AI team is a significant business segment of Honeywell International Inc., focusing on providing innovative AI and software solutions that enhance operational efficiency and drive digital transformation across various industries. Forge is the flagship software product of Honeywell. Forge and AI team, as the AI center of excellence, leverages advanced technologies such as the Internet of Things (IoT), cloud computing, artificial intelligence (AI), and data analytics to create integrated solutions that improve productivity, safety, and sustainability.
Key functions and offerings of Honeywell Forge and AI team include: Industrial IoT Solutions, Data Analytics, Cybersecurity, Smart Building Solutions, Supply Chain Optimization, Sustainability Initiatives, and Smart Manufacturing
We’re looking for a new team member who is motivated by cracking tough challenges with data, trained in problem solving, and with an unending thirst for learning.
As an Advance Data Scientist, you will join a high-performing, global team, and be responsible for designing, developing, and implementing data driven solutions for all Honeywell business groups and functions. You will work closely with data scientists and data engineers, application architects to integrate results into operational platforms
RESPONSIBILITES
- The Advance Data Scientist role is expected to work within Honeywell to build and deploy innovative AI/ML models and solutions that generate new business growth and value.
- You will also be responsible for recommending innovative solutions by using various data science methods including hypothesis testing and be responsible for defining the data acquisition strategy when required.
- You will also be expected to actively participate in defining and governing our analytics strategy for Honeywell building out AI/ML capabilities of our Forge platform and promoting data science methods and processes across functions
- You will report to the Director of Artificial intelligence
YOU MUST HAVE
- Bachelor’s degree in computer science, Engineering, Applied Mathematics or related STEM field
- Minimum of 4 years of full time Data Science prototyping experience (Python) using machine learning techniques and algorithms (supervised, unsupervised, reinforcement learning etc.) in a commercial setup.
- Minimum of 4 years of full time Machine Learning experience applied on top of processes, systems, and hardware in a commercial setup.
- Minimum of 4 years of experience with distributed storage and compute tools (e.g. Spark)
- Minimum of 4 years' experience developing and deploying machine learning models on cloud platforms (e.g. AWS, Azure, GCP etc.)
- Minimum of 4 years of experience in deep learning frameworks like PyTorch, Tensorflow, Keras
- Minimum of 4 years' Experience with designing, building models and deploying pipelines to production using containerized microservices and/or orchestrated batch runs
WE VALUE
- Master's degree in computer science, Engineering, Applied Mathematics or related STEM field
- PhD degree in Computer Science, Engineering, Applied Mathematics or related STEM field
- Experience with MLOPS best practices and implementations
- Experience with LLM and Natural Language Processing models
- Experience working with remote and global teams
- Results driven with a positive can-do attitude
In addition to a competitive salary, leading-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell employees are eligible for a comprehensive benefits package. This package includes employer subsidized Medical, Dental, Vision, and Life Insurance; Short-Term and Long-Term Disability; 401(k) match, Flexible Spending Accounts, Health Savings Accounts, EAP, and Educational Assistance; Parental Leave, Paid Time Off (for vacation, personal business, sick time, and parental leave), and 12 Paid Holidays. For more information visit: Benefits at Honeywell
The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates. Job Posting Date: 03/15/2026
Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. Person, which is defined as, a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status or have the ability to obtain an export authorization.
About UsHoneywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments – powered by our Honeywell Forge software – that help make the world smarter, safer and more sustainable.Skills Required
- Bachelor's degree in Computer Science, Engineering, Applied Mathematics or related STEM field
- Minimum of 4 years full-time data science prototyping experience using Python and ML techniques
- Minimum of 4 years machine learning experience applied to processes, systems, and hardware in a commercial setup
- Minimum of 4 years experience with distributed storage and compute tools (e.g., Spark)
- Minimum of 4 years developing and deploying ML models on cloud platforms (e.g., AWS, Azure, GCP)
- Minimum of 4 years experience in deep learning frameworks such as PyTorch, TensorFlow, Keras
- Minimum of 4 years experience designing, building models and deploying pipelines to production using containerized microservices and/or orchestrated batch runs
- Must be a U.S. Person (U.S. citizen, permanent resident, protected status, or able to obtain export authorization)
- Master's degree in Computer Science, Engineering, Applied Mathematics or related STEM field
- PhD in Computer Science, Engineering, Applied Mathematics or related STEM field
- Experience with MLOps best practices and implementations
- Experience with LLMs and Natural Language Processing models
- Experience working with remote and global teams
