Data Scientist II

As a Data Scientist II at Honeywell in Pune, India, you will be instrumental in developing and implementing sophisticated data analytics models and algorithms to tackle intricate business problems. You will collaborate closely with cross-functional teams, gaining a deep understanding of business requirements and translating them into effective, data-driven solutions. Your role will involve expertly applying machine learning, statistical modeling, and data analysis techniques to uncover actionable insights that generate significant business value.

In this pivotal role, you will directly impact the business by optimizing processes, reducing operational costs, and identifying new growth opportunities through your data-driven insights. Your contributions will be key in positioning Honeywell at the vanguard of data-driven innovation, leveraging state-of-the-art technologies and advanced analytics to propel our business forward.

Key Responsibilities:

• Apply deep expertise in machine learning, statistical modeling, and data analysis to develop and implement advanced algorithms and analytical solutions.
• Manage end-to-end data science projects, ensuring strict alignment with business objectives and the successful delivery of actionable insights.
• Provide mentorship and guidance to junior data scientists, fostering their growth and development.
• Contribute to the strategic vision and direction of the Data Science team.
• Utilize strong analytical and problem-solving skills to address complex data challenges and generate high-value insights.

Qualifications:

YOU MUST HAVE:

• A minimum of 2 years of experience in data analysis, statistical modeling, or a closely related field.
• Proven experience in successfully developing and implementing data science projects from inception to completion.
• Strong project management and organizational abilities to manage multiple tasks efficiently.

WE VALUE:

• A Bachelor's degree or an Advanced degree in Computer Science, Statistics, Mathematics, or a related quantitative discipline.
• Experience in leading and taking ownership of complex data projects.
• Proficiency in programming languages commonly used in data science, such as Python or R.
• Demonstrated strategic thinking capabilities and the ability to align data science initiatives with overarching business objectives.