Sr. Advanced Data Scientist
We are looking for a highly motivated Sr. Advanced Data Scientist who will be a part of HON Buildings Automation team, leading end to end development of complex machine learning solutions ranging from innovating, designing, developing proof of concepts to prototyping and deploying of solutions in the Smart Communities domain with incident management and customizable dashboard capabilities for different user persona. Data involves multi-functional domains ranging from HVAC systems, Fire, security, irrigation etc. Your abilities should also include ability to design effective dashboards and show the live data analytics, alarms and analysis as needed. We want you to demonstrate strong sense of urgency, passion and leadership and drive to make things happen, with skills of segmenting complex problems into smaller problems and solve them with high precision.
ResponsibilitiesKey Responsibilities
Understanding customer requirements and talking to different stakeholders
Architecting AI, ML and Gen AI based solutions that cut across veracity and variety of data including, time series, audio, video, event data, text and numeric data.
Develop end-to-end solutions involving, traditional, predictive and prescriptive Analytics, and Agentic AI solutions, effectively combining data from various sub-systems
Provide technical leadership to a team of data scientists
Own the design, development, completion of the Technology Solutions and follow HON processes
Strong analytical thinking, problem-solving, and a "go-getter" attitude.
Requirements:
Have experience in architecting and completing end-to-end Machine Learning and AI solutions involving multiple kinds of data such as time series, audio, video, event and numeric data, spanning across multiple tools.
Should have handled complete ownership of data analysis & interpretation, implementation of statistical models & ML algorithms and data visualization in projects.
Extensive experience with PyTorch and TensorFlow to design and optimize complex neural architectures like CNNs, RNNs, and Transformers, Mastery of Python and SQL; proficiency in R, Scala, or C++ for high-performance applications.
Frameworks: Deep expertise in PyTorch, TensorFlow, Keras, and Hugging Face.
Cloud & Infrastructure: Hands-on experience with AWS (SageMaker, Athena), Azure, or GCP (Vertex AI).
Big Data: Proficiency with Spark, Databricks, Airflow, and Kafka for large-scale data pipelines.
Tooling: Experience with experiment tracking (WandB, MLflow) and containerization (Docker, Kubernetes).
Data Engineering, ETL, setting up AI / ML pipeline
Agentic AI Frameworks, Proficiency in LangGraph, CrewAI, Microsoft AutoGen, and LlamaIndex Workflows and Tools usage, orchestration of autonomous systems, Multi-Agent Systems.
Multi-Modal AI Models, Language Models and Traditional and Deep Learning AI model training and fine tuning
Safety, Ethics & "AgentOps"
QualificationsYOU MUST HAVE
- B Tech with 8+ years’ experience in AI ML Projects, with specialization in AI/ML, Pattern Recognition etc.
- M Tech with 5 + years experience or a PhD with 3 years’ experience. In the above-mentioned areas.
Skills Required
- B.Tech with 8+ years OR M.Tech with 5+ years OR PhD with 3+ years in AI/ML or related fields
- Proven experience architecting and delivering end-to-end ML and AI solutions for multimodal data (time series, audio, video, event, numeric)
- Expertise in Python and SQL
- Proficiency in R, Scala, or C++ for high-performance applications
- Extensive experience with PyTorch and TensorFlow and designing/optimizing CNNs, RNNs, Transformers
- Deep expertise with frameworks: Keras and Hugging Face
- Cloud experience with AWS (SageMaker, Athena), Azure, or GCP (Vertex AI)
- Big data and pipeline experience: Spark, Databricks, Airflow, Kafka
- Experience with experiment tracking and MLOps tooling: WandB, MLflow, Docker, Kubernetes
- Data engineering and ETL experience; building AI/ML pipelines
- Experience with Agentic AI / multi-agent frameworks and orchestration: LangGraph, CrewAI, Microsoft AutoGen, LlamaIndex
- Experience training and fine-tuning multimodal and language models
- Knowledge of safety, ethics, and AgentOps practices
- Proven ability to provide technical leadership to a team of data scientists
- Ability to design dashboards and visualize live analytics, alarms, and KPIs for multiple user personas
Honeywell Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Honeywell and has not been reviewed or approved by Honeywell.
-
Retirement Support — Retirement plans feature a notably strong company 401(k) match with vesting after three years, enhancing long-term savings security. Additional tax-advantaged accounts and company contributions for eligible earners further strengthen financial preparedness.
-
Leave & Time Off Breadth — Time off policies include flexible or unlimited vacation for many salaried roles and a broad observed-holiday schedule, providing manager-approved flexibility. This structure supports rest and work-life balance across varied needs.
-
Parental & Family Support — Parental leave offers paid time for birth, adoption, or foster care that can be taken consecutively or intermittently. The design enables practical flexibility in how family leave is used.
Honeywell Insights
What We Do
Honeywell is a Fortune 500 company that invents and manufactures technologies to address tough challenges linked to global macrotrends such as safety, security, and energy. With approximately 110,000 employees worldwide, including more than 19,000 engineers and scientists, we have an unrelenting focus on quality, delivery, value, and technology in everything we make and do.
