Sr Advanced Data Scientist
Listed on Honeywell International’s official careers site. Posted October 13, 2026. Check that it is still open and apply there.
Apply on Honeywell International’s careers site →Job description
We are seeking an experienced Advanced Data Scientist to join our AI and Analytics product development team. In this role, you will drive the research, design, development, and deployment of advanced AI-powered solutions leveraging Generative AI, Machine Learning, Deep Learning, and modern Data Engineering technologies. You will work on high-value, complex business challenges, transforming large-scale industrial and enterprise data into actionable insights and intelligent products.
The ideal candidate combines strong expertise in AI/ML model development with robust software engineering and data engineering capabilities, enabling the delivery of scalable, production-grade solutions from concept through deployment.
Responsibilities
Key Responsibilities
Research and apply advancements in Artificial Intelligence, including: Generative AI and Large Language Models (LLMs) Causal AI Knowledge Graphs Machine Learning and Deep Learning Design, develop, and deploy scalable AI/ML solutions that solve complex customer and business problems. Lead research initiatives, proof-of-concepts, pilot programs, and rapid prototyping activities to evaluate emerging technologies and product opportunities.
Build and optimize data pipelines, data engineering workflows, and analytics platforms to support machine learning applications. Process, transform, and prepare structured and unstructured data for advanced analytics and AI model consumption. Collaborate with product managers, domain experts, software engineers, architects, and stakeholders to deliver end-to-end solutions. Perform problem analysis, solution design, development, integration, testing, deployment, maintenance, and support of analytics and AI products.
Establish best practices, standards, and governance processes for AI/ML model development, deployment, monitoring, and lifecycle management. Develop high-quality, maintainable, and testable software using modern engineering practices including automated unit testing and CI/CD. Evaluate and adopt productivity-enhancing tools, frameworks, and emerging technologies to accelerate innovation and delivery.
Qualifications
Required Qualifications
Bachelor's or master’s degree in Engineering, Applied Mathematics, Statistics, or a related discipline. 8 to 14 years of overall experience with at least 4 years of relevant experience in AI/ML, Analytics, Data Science, or Data Engineering product development. Strong analytical and problem-solving skills with the ability to derive insights from complex data. Experience developing and deploying machine learning or AI-based products in production environments.
Experience working in agile product development organizations.
Technical Skills
Artificial Intelligence & Machine Learning Generative AI Large Language Models (LLMs) Machine Learning Deep Learning Statistical Modeling Predictive Analytics Knowledge Graphs Causal AI Model Deployment and Monitoring Programming Advanced Python PySpark Data Engineering Data Processing and Transformation Data Pipeline Development Data Preparation for ML Workloads Python Packaging and Deployment Software Engineering Practices Automated Unit Testing (PyTest) CI/CD and DevOps Practices Git / Bitbucket GitHub Copilot Scalable and Performant Application Design
Preferred Qualifications
Experience working with Industrial Automation, Manufacturing, Process Control, or Industrial IoT data. Experience supporting fast-paced product engineering and innovation teams. Exposure to MLOps, AI platform development, and large-scale distributed data processing. Strong communication, stakeholder management, and cross-functional collaboration skills. Demonstrated ability to learn, explore, and adopt emerging technologies aligned with organizational objectives.
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