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Sr Advanced Data Scientist at Honeywell

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

28 May, 26

Salary

0.0

Posted On

27 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Statistical Modeling, Data Analysis, Project Management, Organizational Abilities, Mentoring, Python, R, Strategic Thinking

Industry

electrical;Appliances;and Electronics Manufacturing

Description

As a Sr Advanced Data Scientist here at Honeywell, you will be responsible for providing technical insight and acting as the subject matter expert in machine learning, statistical modeling, and data analysis projects. You will work closely with leadership to translate business needs into data science solutions. You will be responsible for contributing to the continuous improvement of methodologies and exploring new approaches to enhance analytical capabilities. In this role, you will impact the strategic vision of the Data Science team, providing input on initiatives that align with business objectives. You will lead complex projects, provide technical expertise, and contribute to the strategic vision of the team. Let’s shape the future of how we use data together. 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.

Responsibilities

The Senior Advanced Data Scientist will provide technical insight and act as the subject matter expert in machine learning, statistical modeling, and data analysis projects, working closely with leadership to translate business needs into data science solutions. This role involves leading complex projects, contributing to methodological improvements, and impacting the strategic vision of the Data Science team.