Lead Data Scientist, Honeywell

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 the 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.

Requirements & Skills:

• Bachelor’s degree in computer science, Engineering, Applied Mathematics, or a 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

What we value:

• Master’s degree in computer science, Engineering, Applied Mathematics, or a 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