As a Sr Data Science Supervisor here at Honeywell, you will lead a team of data scientists to drive innovative data solutions that enhance decision-making and operational efficiency across the organization. Your leadership will be crucial in fostering a culture of excellence and collaboration while overseeing the development and implementation of advanced analytics projects.

You will report directly to our Sr. Data Engineering Manager, and you’ll work out of our Bengaluru, India location on a Hybrid work schedule.

In this role, you will impact the organization by guiding your team in leveraging data science techniques to solve complex business challenges, optimize processes, and deliver actionable insights that align with corporate objectives.

Required Qualifications

• Bachelor of Engineering or master’s degree in data science, Computer Science, Statistics, Mathematics, or a related field.
• 10-12+ years of overall experience and 8+ years of relevant experience in data science or advanced analytics roles at least 2 years in a supervisory or leadership role.
• Proven track record of delivering production-grade models and analytics solutions.
• Strong programming skills in Python,SQL, and Py Spark.
• Experience with cloud platforms (Azure, AWS, GCP) and collaborative environments like Databricks.
• Familiarity with MLOps tools and practices (MLflow, CI/CD pipelines, model monitoring).

Preferred Skills

• Expertise in **Generative AI (GenAI)**and Large Language Models (LLMs), including frameworks like Hugging Face, Lang Chain, and OpenAI APIs.
• Experience with deep learning (Tensor Flow, Py Torch) and NLP techniques.
• Strategic thinking and the ability to align data science initiatives with business objectives.
• Ability to design optimal Databricks job clusters and apply performance tuning for scalable analytics workflows.
• Excellent communication and stakeholder management skills.
• Ability to lead without direct reports—driving influence through technical excellence and collaboration.

Your Day-to-Day

• Lead Data Science Projects: Architect large-scale data science initiatives—Collaborate with DE team for building ETL pipelines and deploying advanced analytics models and algorithms.
• Shape the Strategy: Define and execute the data science roadmap, ensuring our analytics capabilities stay ahead of the curve.
• Be a Mentor: Guide and support a team of data scientists, setting technical direction and sharing your expertise.
• Partner with Stakeholders: Work closely with business leaders to align analytics efforts with strategic goals.
• Prioritize What Matters: Manage the data science backlog and ensure the team is focused on the highest-impact work.
• Drive Innovation: Explore and apply new technologies—like LLMs and GenAI—to push the boundaries of what’s possible.