Lead Data Scientist

Innovate to solve the world's most important challenges

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 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 Connected Enterprise 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 a Lead 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 application architects to integrate results into operational platforms.

Key Responsibilities:

• The Lead 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 lead 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.

#LI-HYBRID

MUST HAVE:

• Bachelor 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 etc.) in a commercial setup.
• Minimum of 7 years of full time Machine Learning experience applied on top of processes, systems, and hardware in a commercial setup.
• Minimum of 6 years of experience with distributed storage and compute tools (e.g. Spark)
• Minimum of 6 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

Additional Information

• JOB ID: HRD9085991
• Category: Engineering
• Location: 715 Peachtree Street, N.E.,Atlanta,Georgia,30308,United States
• Exempt

Honeywell is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status.