We re looking for a new team member for our Global Finance analytics team who is motivated by cracking tough challenges with data, trained in problem solving, and with an unending thirst for learning.
As an AI Engineer II, you will join a high-performing, global team, and be responsible for developing, and deploying data driven solutions for all Honeywell business groups and functions. You will work closely with application architects to integrate results into operational platforms, including Hadoop and NoSQL architectures.
You will also be responsible for researching, training and deploying data science models like Time Series Forecasting, Regression, NLP, Classification models and industry exposure to Gen AI
You will be expected to show willingness to learn and grow and work closely with Senior members in the team to bring new ideas and cutting edge data science frameworks to table.
You will report to the Global Data Science Leader for Digital Finance.
You must have:
Master s degree in computer science, Engineering, Applied Mathematics or related field
Minimum of 2-3 years of experience in implementing, deploying and monitoring ML Pipelines
Minimum of 2-3 years of experience in CI/CD pipeline management and automation
Minimum of 1-2 years of experience in deploying large ML models into clouds platforms like Databricks, Azure etc.
Minimum of 2-3 years of hands-on experience in programming languages like python, Spark
Minimum of 1-2 years of Data Science prototyping experience (Python and/or R tool-stack) using machine learning techniques and algorithms such as Time Series Modeling and Forecasting, NLP, Clustering, Classification, Regression
Minimum of 1-2 years of Machine Learning experience of physical systems
Minimum of 1 year of experience with distributed storage and compute tools (e.g. Hive and Spark)
Experience with designing, building models and deploying pipelines to production using containerized microservices like Kubernetes and dockers.
We value:
Master s degree in computer science, Engineering, Applied Mathematics or related field
Exposure to Finance domain and use cases in larger global enterprise setting
Experience with Generative AI, Financial Analytics, Finance Modeling
