Engineer

Data Science Engineer - Intelligent Power Solutions in Pune

Eaton Corporation's Center for Intelligent Power is seeking a passionate Data Scientist to join our team in Pune. This role is instrumental in designing and developing cutting-edge ML/AI algorithms to address complex power management challenges. Beyond algorithm development, you will be involved in the seamless integration of these solutions into edge and cloud systems, leveraging CI/CD pipelines and adhering to robust software release processes.

Key Responsibilities:

• Drive project success through exceptional architecture, technical deliverables, and project management across the entire lifecycle, utilizing Agile methodologies and tools.
• Apply expertise in data analysis, ML/AI model development, and associated development environments to deploy algorithms on diverse processors and systems.
• Collaborate with a multidisciplinary team of experts in deep learning, machine learning, distributed systems, program management, and product development to design, build, and deliver end-to-end data science pipelines and solutions.
• Develop innovative technical solutions and implement robust architectures for projects and products, working in tandem with data engineering and data science teams.
• Contribute to the architecture, design, and development of new intelligent power technology products and production-quality end-to-end systems.

Qualifications:

• Master's degree in Data Science or a Ph.D. (ongoing) in Data Science.
• Minimum of 2 years of progressive experience delivering technology solutions in a production environment.
• Over 2 years of practical data science experience, applying statistics, machine learning, and analytic approaches to solve critical business problems and identify new opportunities.
• 2 years of experience working with internal and external customers to define requirements and act as a solutions architect.

Required Skills:

• Strong statistical foundation, including Bayesian networks and hypothesis testing.
• Proficiency in developing Deep Learning and Machine Learning models for engineering applications such as electrical/electronic systems, energy systems, data centers, and mechanical systems.
• Hands-on experience with ML/DL models for time series analysis, anomaly detection, root cause analysis, diagnostics, prognostics, pattern recognition, and data mining.
• Familiarity with data visualization tools and techniques.
• Programming expertise in Python, R, Matlab, C/C++, Java, PySpark, and SparkR.
• Experience with Azure ML Pipeline, Databricks, and MLFlow.
• Knowledge of optimization techniques such as dynamic programming and particle swarm optimization.
• Understanding of the Software Development Life Cycle (SDLC) processes and tools.
• Experience with Agile development methodologies and tools like Jira, Bitbucket, and Confluence.