As a Sr Advanced Data Scientist here at Honeywell, you will leverage your expertise in advanced analytics and data science to develop innovative solutions that drive business growth and operational efficiency. You will work on complex data sets and cutting-edge technologies to extract actionable insights that influence strategic decisions.
You will work out of our Atlanta, GA location on a hybrid work schedule.
In this role, you will impact the company's ability to harness data-driven insights to optimize processes, enhance product offerings, and contribute to Honeywell's leadership in technology innovation.
KEY RESPONSIBILITIES
- The Sr Advanced Data Scientist role is expected to work within Honeywell to identify opportunities for new growth and efficiency based on data analyses and foster relationships with business team members by being proactive, displaying a thorough understanding of the business processes.
- You will also be responsible for recommending innovative solutions by using various data science methods including hypothesis testing and also be responsible for defining the data acquisition strategy when required.
- After influencing scope and prioritizing the analytics pipeline, you will assist in leading the technical execution of data science projects directing daily work of junior data scientists and will be responsible for the overall success of the project. This includes stakeholder management by presenting regular updates and final results to senior leadership of the customer organization.
- 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 Data Science Leader in Honeywell Connected Enterprise.
- 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 3 years of experience with distributed storage and compute tools (e.g. Spark)
- Minimum of 3 years' experience developing and deploying machine learning models on cloud platforms (e.g. AWS, Azure, GCP etc.)
- Minimum of 2 years of experience in deep learning frameworks like PyTorch, Tensorflow, Keras
- Minimum of 2 years' Experience with designing, building models and deploying pipelines to production using containerized microservices and/or orchestrated batch runs
- Bachelor’s degree or Advanced degree in Computer Science, Statistics, Mathematics, or related discipline.
- 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 OF WORKING FOR HONEYWELL
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: click here
The application period for the job is estimated to be 40 days from the job posting date August 14, 2026; however, this may be shortened or extended depending on business needs and the availability of qualified candidates.
ABOUT HONEYWELLHoneywell International Inc. (Nasdaq: HON) invents and commercializes technologies that address some of the world's most critical challenges around energy, safety, security, air travel, productivity, and global urbanization. We are a leading software-industrial company committed to introducing state of the art technology solutions to improve efficiency, productivity, sustainability, and safety in high growth businesses in broad-based, attractive industrial end markets. Our products and solutions enable a safer, more comfortable, and more productive world, enhancing the quality of life of people around the globe. Learn more about Honeywell: click here
THE BUSINESS UNIT
Honeywell Advanced Materials is an industry leading solutions provider, playing a crucial role in advancing industries worldwide through diverse applications, revolutionary inventions, and pioneering technologies focused on high growth mega-trends. Our science and technology experts create solutions that help solve our customers' needs today and in the future. Our solutions span across industries, including retail, healthcare and pharma, buildings, manufacturing and hi-tech. In each of these verticals we bring deep materials and engineering knowledge, which leads to our customers achieving reduction in energy consumption, cutting down their carbon emissions and improving their operational efficiencies.
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
- Minimum 4 years full-time Data Science prototyping experience using Python and ML techniques (supervised, unsupervised, reinforcement learning) in a commercial setup.
- Minimum 4 years full-time Machine Learning experience applied to processes, systems, and hardware in a commercial setup.
- Minimum 3 years experience with distributed storage and compute tools (e.g., Spark).
- Minimum 3 years experience developing and deploying machine learning models on cloud platforms (e.g., AWS, Azure, GCP).
- Minimum 2 years experience with deep learning frameworks such as PyTorch, TensorFlow, Keras.
- Minimum 2 years experience designing, building models and deploying pipelines to production using containerized microservices and/or orchestrated batch runs.
- Bachelor's, Master's, or PhD in Computer Science, Statistics, Mathematics, or related discipline.
- 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.
Honeywell Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Honeywell and has not been reviewed or approved by Honeywell.
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Retirement Support — Retirement plans feature a notably strong company 401(k) match with vesting after three years, enhancing long-term savings security. Additional tax-advantaged accounts and company contributions for eligible earners further strengthen financial preparedness.
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Leave & Time Off Breadth — Time off policies include flexible or unlimited vacation for many salaried roles and a broad observed-holiday schedule, providing manager-approved flexibility. This structure supports rest and work-life balance across varied needs.
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Parental & Family Support — Parental leave offers paid time for birth, adoption, or foster care that can be taken consecutively or intermittently. The design enables practical flexibility in how family leave is used.
Honeywell Insights
What We Do
Honeywell is a Fortune 500 company that invents and manufactures technologies to address tough challenges linked to global macrotrends such as safety, security, and energy. With approximately 110,000 employees worldwide, including more than 19,000 engineers and scientists, we have an unrelenting focus on quality, delivery, value, and technology in everything we make and do.
