Associate Engineer- Data Science

Role Overview: As a Data Scientist at Eaton Corporation's Center for Intelligent Power, you will play a crucial role in designing and developing ML/AI algorithms to address power management challenges. You will also contribute to the successful integration of these algorithms in edge or cloud systems using CI/CD and software release processes. Your impact will be significant in delivering projects through architecture, technical deliverables, and project delivery, demonstrating expertise in Agile methodologies and tools. You will collaborate with a team of experts in deep learning, machine learning, distributed systems, program management, and product teams to design, develop, and deliver end-to-end pipelines and solutions. Additionally, you will be involved in developing technical solutions and implementing architectures for projects and products alongside data engineering and data science teams. Key Responsibilities: - Develop ML/AI algorithms for power management problem-solving - Integrate algorithms in edge or cloud systems using CI/CD and software release processes - Collaborate with cross-functional teams to design, develop, and deliver end-to-end solutions - Participate in the architecture, design, and development of new intelligent power technology products and systems Qualifications: - Bachelor's degree in Data Science, Electrical Engineering, Computer Science, or Electronics Engineering - 0-1+ years of practical data science experience applying statistics, machine learning, and analytic approaches to solve critical business problems and identify new opportunities Additional Details: - Excellent verbal and written communication skills are required, including the ability to communicate technical concepts effectively within virtual, global teams. - Good interpersonal, negotiation, and conflict resolution skills are necessary. - Ability to understand academic research and apply new data science techniques is essential. - Experience working with global teams and established big data platform practices is preferred. - Innate curiosity and a self-directed approach to learning are valued traits in a team player. Qualification Required: - Good Statistical background such as Bayesian networks, hypothesis testing, etc. - Hands-on experience with ML/DL models such as time series modeling, anomaly detection, root cause analysis, diagnostics, prognostics, pattern detection, data mining, etc. - Knowledge of data visualization tools and techniques - Programming Knowledge in Python, R, Matlab, C/C++, Java, PySpark, SparkR - Familiarity with Azure ML Pipeline, Databricks, MLFlow, SW Development life-cycle process & tools Desired Skills: - Knowledge of Computer Vision, Natural Language Processing, Recommendation AI Systems - Familiarity with traditional and new data analysis methods for building statistical models and discovering patterns in data - Understanding of open source projects like Open CV, Gstreamer, OpenVINO, ONNX, Tensor flow, Pytorch, and Caffe - Proficiency in Tensor Flow, Scikit, Keras, Spark ML, Numpy, Pandas - Advanced degree and/or specialization in related discipline (e.g., machine learning),