As an Advanced Data Scientist at Honeywell, you will provide technical leadership in machine learning, statistical modeling, and data analysis while translating business needs into scalable data science solutions. Based in Pune, Maharashtra, you will lead end-to-end analytical initiatives, contribute to evolving methodologies, and mentor junior data scientists to strengthen team capability and innovation.
Key Responsibilities
- Conduct research aligned to product and technology roadmaps to mature and apply advanced AI concepts, including generative AI, causal methods, knowledge graphs, machine learning, and deep learning.
- Research, design, and implement scalable AI-based solutions that solve high-value customer problems and support new growth opportunities.
- Lead prototyping and what-if explorations that support pilot programs and R&D initiatives.
- Collaborate with cross-functional teams to develop data-driven solutions and translate business requirements into analytical approaches.
- Design, develop and implement robust and scalable Python based applications. Need to work closely with cross-functional teams to understand requirements, analyse data, and provide technical solutions to address business needs
- Own problem analysis, stakeholder interaction, solution design, integration, maintenance, and support for data science and analytics solutions.
- Develop guidelines and standards for analytics and machine learning models, including deployment practices and associated processes.
- Mentor junior data scientists and contribute to a collaborative, innovative team culture.
- Stay abreast of the latest developments in process control technologies and industry best practices.
Preferred Qualifications
- Chemical engineering background or APC/APM experience is an advantage.
- Experience supporting fast-paced engineering teams.
- Hands-on experience in design and development, including automated unit testing with pytest, and a strong technical foundation for building performant, extendable applications.
- Experience in the industrial automation domain.
- Knowledge of packaging Python applications.
- Preferred development experience with agile methodologies.
- Understanding of version control and development toolchains, including Git, Bitbucket, DevOps toolsets, and GitHub Copilot.
- Ability to use productivity-enhancing tools to support faster delivery and broader feature development.
- Willingness to explore and adopt new trends while aligning with organizational goals.
- Strong analytical, technical, interpersonal, and independent working skills, with the ability to collaborate effectively as a team player.