Engineer

What you’ll do:

Eaton Corporation's Center for Intelligent Power is seeking a passionate Data Scientist to join their team. This Data Science Engineer will be instrumental in designing and developing Machine Learning/Artificial Intelligence (ML/AI) algorithms to address complex power management challenges. Beyond algorithm development, the role involves the successful integration of these algorithms into edge or cloud systems, leveraging Continuous Integration/Continuous Deployment (CI/CD) and software release processes.

The ideal candidate will demonstrate significant impact in project delivery, encompassing architecture, technical deliverables, and overall project lifecycle management. Familiarity with Agile methodologies and tools is expected.

Experience in data analysis, ML/AI model development, and the associated development environments that enable ML/AI algorithms for various processors or systems is crucial.

Collaboration with a team of experts in deep learning, machine learning, distributed systems, program management, and product teams is a key aspect of this role, covering all facets of designing, developing, and delivering end-to-end pipelines and solutions.

This position involves developing technical solutions and implementing architectures for projects and products in conjunction with data engineering and data science teams.

Participation in the architecture, design, and development of new intelligent power technology products and production-ready end-to-end systems is a core responsibility.

Qualifications:

• Bachelor's/Master's degree in Data Science or Ph.D. (ongoing) in Data Science.
• 2+ years of progressive experience in delivering technology solutions within a production environment.
• 2+ years of practical data science experience applying statistics, machine learning, and analytic approaches, with a proven record of solving critical business problems and identifying new business opportunities.
• 2 years of experience working with internal and external customers on requirement development and serving as a solutions architect.
• Master's in Data Science or pursuing a Ph.D. in Data Science, or an equivalent qualification.

Skills:

• Strong statistical foundation, including areas like Bayesian networks and hypothesis testing.
• Hands-on experience developing Deep Learning and Machine Learning models for engineering applications such as electrical/electronic systems, energy systems, data centers, and mechanical systems.
• Practical experience with ML/DL models for time series modeling, anomaly detection, root cause analysis, diagnostics, prognostics, pattern detection, and data mining.
• Proficiency in data visualization tools and techniques.
• Programming skills 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 Software Development Life Cycle (SW Development life-cycle) processes and tools.
• Experience with Agile development methodologies and concepts, including hands-on use of Jira, Bitbucket, and Confluence.