Honeywell is looking for a Sr Data Scientist and AI Developer to design and implement advanced data solutions for AI. In this role, you will leverage your technical skills to develop innovative software solutions that support strategic initiatives, enhance decision-making, and improve operational efficiency across all AI modalities and data types.
What You'll Do
- Design, develop, and deploy advanced machine learning models, LLM-based solutions, and agentic AI systems to solve complex business problems.
- 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 into clear business recommendations and decision frameworks.
- Stay current with emerging trends in AI and assess applicability within the enterprise.
- Contribute to reusable AI assets such as feature stores, embedding stores, evaluation datasets, agent toolkits, and documentation playbooks.
What We're Looking For
- 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.
Nice to Have
- 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.
Technical Stack
- Languages & Core Libraries: Python, pandas, NumPy, scikit‑learn, PyTorch or TensorFlow, HuggingFace Transformers
- Platforms & Tools: Databricks, Spark, Delta Lake, Unity Catalog, MLflow, Dataiku, Tableau
- AWS Services: S3, Lambda, Step Functions, Glue, Bedrock, SageMaker
Team & Environment
You will report directly to our AI Director.
Benefits & Compensation
- Employer-subsidized Medical, Dental, Vision, and Life Insurance
- Short-Term and Long-Term Disability
- 401(k) match
- Flexible Spending Accounts
- Health Savings Accounts
- EAP
- Educational Assistance
- Parental Leave
- Paid Time Off (for vacation, personal business, sick time, and parental leave)
- 12 Paid Holidays
Work Mode
This is a hybrid position based in Phoenix, AZ.
Honeywell is an equal opportunity employer.
