Honeywell

dvanced Data Scientist for Honeywell International, Inc. in Atlanta, GA R

esponsibilities: R

• esponsible for leading technical machine learning projects and provide direction on exploring and implementing methodologies. D
• rive machine learning operation best practices across Forge Insight team and Honeywell. L
• ead critical machine learning initiatives and drive technical excellence within the organization. F
• unction as an AI/ML expert and drive Forge Insight team to continue perform as AL Center of Excellence for Honeywell. D
• rive requirement for the Forge platform development to ensure it meets the AI/ML specifications and functional need. W
• ork with Engagement managers to translate business requirements to technical tasks. D
• rive collaboration with colleagues across multiple function groups (Data Science, Data Engineering, domain experts) on unique challenges across different business units of Honeywell. M
• entor entry level data scientists, machine learning engineers and data engineers to groom their technical skill for future development. L
• ead by example with upskilling as part of the AI/ML upskilling program of HCE. D
• evelop complicated, scalable and robust analytics solutions to solve business problems. L
• everage distributed training systems to build scalable machine learning pipelines for model training and deployments in IT/OT Products space. D
• esign and implement solutions to optimize distribute training execution in terms of model hyperparameter optimization, model training/inference latency and system-level bottlenecks. E
• nsure ML Model performance, uptime, and scale, maintaining high standards of code quality and thoughtful design quality and monitoring. O
• ptimize integration between popular machine learning libraries and cloud ML and data processing frameworks. L
• ead technical discussion, evaluate, visualize and communicate the AI/ML model results and correlation with business KPI’s. W
• ork within project planning constraints, communicating any identified project risks and issues to the delivery/project manager and provide inputs to the change control process. W
• ork closely with the operations team to change, optimize existing Automation and AI/ML processes and help build effective model performance monitoring, alert and notification framework to proactively identify problems/issues.

OU MUST HAVE: Q

• ualified applicants must have a Master’s degree or foreign equivalent in Computer Science, Data Science, Engineering, or a related field and 2 years of experience with data science development, deployment in a commercial setup. F
• ull term of experience must include: Programming Proficiency in Python/R and SQL; MachineLearning: Regression, random foreast, Xgboost, neural networks (RNN, GNN etc), MLOps, SVM, hyperparameter tuning, forecasting (arima, LSTM etc.), Optimization, Predictive Analytics, deep learning, Pytorch, tensorflow, keras; Stack proficiency with Azue and Databricks; experience in developing production level codebase leveraging standard practices including but not limited to the use of object oriented programming and version control; excellent understanding of Machine Learning techniques and proficiency in feature analysis, algorithm selection and model hyperparameter tuning. T
• elecommuting permitted two times per week.