Honeywell
Overview
Honeywell Connected Enterprise (HCE) is a significant business segment of Honeywell International Inc., focusing on providing innovative software solutions that enhance operational efficiency and drive digital transformation across various industries. HCE leverages 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. We are seeking a Lead Data Scientist to join a high-performing, global team to design, develop, and implement data-driven solutions for all Honeywell business groups and functions. You will work closely with application architects to integrate results into operational platforms. Due to compliance with U.S. export control laws and regulations, candidates must be a U.S. Person (US citizen, US permanent resident, or have protected status in the U.S.) or able to obtain the necessary export authorization. Key Responsibilities Identify opportunities for growth and efficiency based on data analyses; foster relationships with business teams by demonstrating a thorough understanding of business processes. Recommend innovative solutions using various data science methods, including hypothesis testing; define data acquisition strategy when required. Lead the technical execution of data science projects after scoping and prioritizing the analytics pipeline; supervise daily work of junior data scientists and ensure project success; manage stakeholders by presenting updates and final results to senior leadership. Define and govern Honeywell's analytics strategy for building out AI/ML capabilities for the Forge platform; promote data science methods and processes across functions. Report to the Data Science Leader in Honeywell Connected Enterprise.
Qualifications
MUST HAVE: Bachelor's degree in computer science, engineering, applied mathematics or related STEM field. Minimum of 7 years of full-time data science prototyping experience (Python) using machine learning techniques and algorithms (supervised, unsupervised, reinforcement learning) in a commercial setting. Minimum of 7 years of full-time machine learning experience applied to processes, systems, and hardware in a commercial setting. Minimum of 6 years of experience with distributed storage and compute tools (e.g., Spark). Minimum of 6 years' experience developing and deploying ML models on cloud platforms (e.g., AWS, Azure, GCP). Minimum of 4 years of experience with deep learning frameworks (PyTorch, TensorFlow, Keras). Minimum of 4 years' experience designing, building models and deploying production pipelines using containerized microservices and/or orchestrated batch runs.
We Value
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. Results-driven with a positive can-do attitude.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Appliances, Electrical, and Electronics Manufacturing
#J-18808-Ljbffr
Honeywell Connected Enterprise (HCE) is a significant business segment of Honeywell International Inc., focusing on providing innovative software solutions that enhance operational efficiency and drive digital transformation across various industries. HCE leverages 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. We are seeking a Lead Data Scientist to join a high-performing, global team to design, develop, and implement data-driven solutions for all Honeywell business groups and functions. You will work closely with application architects to integrate results into operational platforms. Due to compliance with U.S. export control laws and regulations, candidates must be a U.S. Person (US citizen, US permanent resident, or have protected status in the U.S.) or able to obtain the necessary export authorization. Key Responsibilities Identify opportunities for growth and efficiency based on data analyses; foster relationships with business teams by demonstrating a thorough understanding of business processes. Recommend innovative solutions using various data science methods, including hypothesis testing; define data acquisition strategy when required. Lead the technical execution of data science projects after scoping and prioritizing the analytics pipeline; supervise daily work of junior data scientists and ensure project success; manage stakeholders by presenting updates and final results to senior leadership. Define and govern Honeywell's analytics strategy for building out AI/ML capabilities for the Forge platform; promote data science methods and processes across functions. Report to the Data Science Leader in Honeywell Connected Enterprise.
Qualifications
MUST HAVE: Bachelor's degree in computer science, engineering, applied mathematics or related STEM field. Minimum of 7 years of full-time data science prototyping experience (Python) using machine learning techniques and algorithms (supervised, unsupervised, reinforcement learning) in a commercial setting. Minimum of 7 years of full-time machine learning experience applied to processes, systems, and hardware in a commercial setting. Minimum of 6 years of experience with distributed storage and compute tools (e.g., Spark). Minimum of 6 years' experience developing and deploying ML models on cloud platforms (e.g., AWS, Azure, GCP). Minimum of 4 years of experience with deep learning frameworks (PyTorch, TensorFlow, Keras). Minimum of 4 years' experience designing, building models and deploying production pipelines using containerized microservices and/or orchestrated batch runs.
We Value
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. Results-driven with a positive can-do attitude.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Appliances, Electrical, and Electronics Manufacturing
#J-18808-Ljbffr