As a Sr Data Scientist and AI Developer here at Honeywell, you will play a crucial role in designing and implementing advanced data solutions for AI solutions that drive business insights, enhance decision-making processes and empower AI solutions. Your expertise will help in critical AI development activities across all AI modalities (classic, Gen and agentic) and data @types (structured and unstructured).
You will report directly to our AI Director and you'll work out of our Phoenix, AZ location on a Hybrid work schedule. Note: New Hires will work onsite M-F for the first 90 days.
In this role, you will impact the organization by leveraging your technical skills to develop innovative software solutions that support strategic initiatives and improve operational efficiency.
KEY RESPONSIBILITIES
Design, develop, and deploy advanced machine learning models , LLM-based solutions , and agentic AI systems to solve complex business problems across diverse domains.
Conduct exploratory data analysis, statistical assessments, and feature engineering on structured, semi-structured, and unstructured datasets.
Build and evaluate GenAI workflows including prompt engineering, fine-tuning, RAG pipelines, embedding analysis, and @context optimization.
Develop and validate agentic AI behaviors , including reasoning chains, tool-use strategies, action planning, memory utilization, and safety constraints.
Partner with Data Engineers, AI Developers, Platform Engineers, and MLOps to bring models and agents into production using Databricks, Dataiku, MLflow, and AWS-native deployment patterns.
Develop robust evaluation frameworks for ML models, LLMs, and agentic systems-covering accuracy, robustness, hallucination resistance, safety, bias, reliability, and task success rate.
Implement experiments, compare algorithms, perform ablation studies, and use statistical methods to quantify improvements for both classic ML and LLM-based systems.
Translate complex AI insights (predictions, feature impacts, agent decisions, retrieval @context) into clear business recommendations and decision frameworks.
Stay current with emerging trends in AI-including new model families, multi-modal approaches, vector search innovations, and agentic frameworks-and assess applicability within the enterprise.
Contribute to reusable AI assets such as feature stores, embedding stores, evaluation datasets, agent toolkits, and documentation playbooks.
YOU MUST HAVE
Bachelor's degree from an accredited institution in a technical discipline such as science, technology, engineering, mathematics.
4-7 years of experience building, evaluating, and deploying machine learning models in production environments.
Strong proficiency in Python and key ML/AI libraries (pandas, NumPy, scikit-learn, PyTorch or TensorFlow, HuggingFace Transformers).
Applied experience developing LLM-based solutions , including prompt engineering, retrieval-augmented generation (RAG), embeddings, and evaluation.
Experience working with Databricks (Spark, Delta Lake, Unity Catalog, MLflow) for data preparation, training, and experiment tracking.
Experience with Dataiku for workflow orchestration, data pipelines, and model deployment/use in AI applications.
Hands-on experience with AWS data and AI services such as S3, Lambda, Step Functions, Glue, Bedrock, or SageMaker.
Strong statistical background with experience in hypothesis testing, regression, clustering, classification, and optimization techniques.
Ability to communicate complex findings clearly to technical and non-technical stakeholders.
Proven ability to collaborate in cross-functional agile teams, partnering with engineering, MLOps, and product owners.
WE VALUE
Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative discipline.
Experience with agentic AI systems , including:
Tool/function calling
Multi-step reasoning evaluation
Memory and retrieval strategies
Human-in-the-loop review patterns
Safety and guardrail testing
Experience evaluating LLMs for accuracy, hallucination, chain-of-thought, content safety, and task reliability.
Familiarity with vector databases (Databricks Vector Search, OpenSearch, Pinecone, Milvus) and semantic search techniques.
Experience analyzing and preparing multi-modal datasets (text, images, audio, PDFs) for AI solutions.
Knowledge of ML governance, responsible AI principles, bias detection, model explainability, and compliance considerations.
Strong storytelling, data visualization, and dashboarding skills (Tableau or equivalent).
Curiosity, experimentation mindset, and the drive to push forward the boundaries of applied AI across classic, GenAI, and agentic approaches.
BENEFITS OF WORKING FOR HONEYWELL
In addition to a competitive salary, leading-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell employees are eligible for a comprehensive benefits package. This package includes employer-subsidized Medical, Dental, Vision, and Life Insurance; Short-Term and Long-Term Disability; 401(k) match, Flexible Spending Accounts, Health Savings Accounts, EAP, and Educational Assistance; Parental Leave, Paid Time Off (for vacation, personal business, sick time, and parental leave), and 12 Paid Holidays. For more information visit: click here (https://benefits.honeywell.com/)
The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates. Posting Date: February 18, 2026
US PERSON REQUIREMENT
Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. person, which is defined as, a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status.
ABOUT HONEYWELL
Honeywell International Inc. (Nasdaq: HON) invents and commercializes technologies that address some of the world's most critical challenges around energy, safety, security, air travel, productivity, and global urbanization. We are a leading software-industrial company committed to introducing state-of-the-art technology solutions to improve efficiency, productivity, sustainability, and safety in high growth businesses in broad-based, attractive industrial end markets. Our products and solutions enable a safer, more comfortable, and more productive world, enhancing the quality of life of people around the globe. Learn more about Honeywell: click here (https://www.honeywell.com/us/en)
THE BUSINESS UNIT
Honeywell Aerospace Technologies (AT) products and services are found on virtually every commercial, defense, and space aircraft in the world. We build aircraft engines, cockpit and cabin electronics, wireless connectivity systems, mechanical components and more, and connect many of them via our high-speed Wi-Fi offerings. Our solutions create healthier air travel, more fuel-efficient and better-maintained aircraft, more direct and on-time flight arrivals, safer skies and airports, and more comfortable flights, along with several innovations and services that reflect exciting and emerging new transportation methods such as autonomous and supersonic flight. Revenues in 2023 for Honeywell Aerospace Technology were $14B and there are approximately 21,000 employees globally. To learn more, please visit click here (https://aerospace.honeywell.com/) .
AERO26
Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments - powered by our Honeywell Forge software - that help make the world smarter, safer and more sustainable.
Honeywell is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status.
