Honeywell Lead SW Architect –Analytics 

United States 

533002796

Implementation of end-to-end statistical/ML/analytics solutions as per the industry standard process, CRISP-DM

Understand business requirements and propose suitable solutions

Explore, devise and implement AI algorithm stack

Experiment, prototype and finalize specific solution with the best business metrics

Design and implement architecture/tech stack for data integration, data flow and data storage for ML solutions

Collaborate with product teams across the organization for deployment and integration of AI solutions in existing products

Deliver production quality, modular and reproducible code

Create data visualizations to visualize raw data and analytics insights to demonstrate efficacy of the solution.

Data storytelling to articulate outcomes to non-technical stakeholders.

Solid understanding of statistics, probability, ML and DL

Overall 12+ years of industry experience with a minimum of 7 years of experience in developing and deploying end-to-end AI/ML solutions in production environment

Exposure to generative AI, reinforcement learning, supervised and unsupervised algorithms, various architectures of neural networks, time series forecasting, deep learning networks

Deep expertise in any specific application of ML and DL

Prior experience in building and deploying ML pipelines from data ingestion, preparation to deploying models in production

An understanding of various databases relational, NoSQL with prior experience in any DB

Exposure to ML and DL frameworks like TensorFlow, PyTorch, Caffe, etc

Familiarity with ML testing and data validation frameworks

Cloud programming experience on Azure

Familiarity with IoT communication protocols like MQTT

Edge AI deployment experience