Advanced Data Scientist

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

Qualifications YOU MUST HAVE

• Bachelor’s degree in Computer Science, Engineering, Applied Mathematics, or a related STEM field.
• 4+ years of commercial Data Science and Machine Learning experience using Python and machine learning techniques.
• 4+ years of experience with distributed computing tools (e.g., Spark), cloud platforms (AWS, Azure, GCP), and deep learning frameworks such as PyTorch, TensorFlow, or Keras.
• 4+ years of experience developing, deploying, and maintaining production machine learning models and pipelines, including containerized and batch-processing solutions.

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

Benefits 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: September 25th, 2026.

About Honeywell Technologies Honeywell Technologies is a global, pure-play automation company with a legacy of innovating to help solve the world’s most mission-critical challenges, enhancing the quality of life for people and communities around the world. We serve the building, industrial, and process sectors with a broad portfolio of services, solutions, and products, underpinned by our Honeywell Technologies Accelerator operating system and Honeywell Technologies Forge intelligence layer. By combining the deep domain expertise of our more than 50,000 employees with decades of data from our global installed base, we are uniquely positioned to lead the industrial sector’s transition from automation to autonomy. Learn more

THE BUSINESS UNIT To unlock the next level of value, businesses are ramping up efforts to profitably improve safety, sustainability, and productivity with intelligent autonomous operations. This is a journey of increasing digital maturity fueled by improved intelligence with AI-embedded operations. To reach this goal, industrial companies need industrial-grade software that enables the delivery of domain-specific outcomes. Honeywell Connected Enterprise (HCE) offers industrial operations products that drive outcomes for asset reliability, safety, competency, and productivity, end-to-end process optimization, OT cybersecurity, sustainability, and operational excellence. Honeywell Connected Enterprise provides enterprise and site-specific solutions designed to improve performance, reach sustainability goals, and craft a rock-solid security network.

About Us Honeywell Technologies is a global, pure-play automation company with a legacy of innovating to help solve the world’s most mission-critical challenges, enhancing the quality of life for people and communities around the world. We serve the building, industrial and process sectors with a broad portfolio of services, solutions and products, underpinned by our Honeywell Technologies Accelerator operating system and Honeywell Technologies Forge intelligence layer. By combining the deep domain expertise of our more than 50,000 employees with decades of data from our global installed base, we are uniquely positioned to lead the industrial sector’s transition from automation to autonomy.