Engineer - Data Science

Eaton Corporation; Pune District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Eaton Corporation’s Center for Intelligent Power is seeking a Data Scientist who will design and develop ML/AI algorithms for power management problems. You will integrate these solutions into edge or cloud systems using CI/CD and robust release processes.

You will work with experts in deep learning, data engineering, and product teams to deliver end-to-end pipelines and production-grade systems across agile environments.

Qualifications

• Master’s Degree in Data Science or equivalent.
• ,
• 2+ years of progressive experience delivering technology solutions in production.
• 2+ years practical data science in statistics, ML, and analytics with business impact.
• Experience working with customers as a solutions architect to deliver.

Responsibilities

• Design and develop ML/AI algorithms for power management problems.
• Integrate algorithms into edge or cloud systems using CI/CD and release processes.
• Collaborate with deep learning, data engineering, and product teams across projects.
• Contribute to architecture, design, and end-to-end delivery of systems.

Skills

ML/DL development

Python

Azure ML

CI/CD

Data analysis

Edge/Cloud deployment

Agile

Communication

Team collaboration

Statistical methods

Education

Master's Degree in Data Science

Tools

TensorFlow

PyTorch

Scikit-Learn

Keras

Azure ML Pipeline

Databricks

MLflow

OpenCV

Job description

What you’ll do:

Eaton Corporation’s Center for Intelligent Power has an opening for a Data Scientist who is passionate about his or her craft. The Data Science Engineer will be involved in the design and development of ML/AI algorithms to solve power management problems. In addition to developing these algorithms, the Data Science Engineer will also be involved in successful integration of algorithms in edge or cloud systems using CI/CD and software release process.

• The candidate will demonstrate exceptional impact in delivering projects in terms of architecture, technical deliverables and project delivery throughout the project lifecycle. The candidate is expected to be conversant with Agile methodologies and tools.
• Experience on data analysis, ML/AI model development and related development environment that enables ML/AI algorithms for use on various processors or systems.
• Work with a team of experts in deep learning, machine learning, distributed systems, program management, and product teams, and work on all aspects of design, development and delivery of end-to-end pipelines and solutions.
• Development of technical solutions and implement architectures for project and products along with data engineering and data science teams.
• Participate in architecture, design, and development of new intelligent power technology products and production quality end-to-end systems.

Qualifications:

• Master’s Degree in Data Science.
• 2+ years of progressive experience in delivering technology solutions in a production environment.
• 2+ years of practical data science experience in the application of statistics, machine learning, and analytic approaches with a proven track record of solving critical business problems and uncovering new business opportunities.
• 2+ years working with customers (internal and external) on developing requirements and working as a solutions architect to deliver.

Skills:

• Good statistical background such as Bayesian networks, hypothesis testing, etc.
• Hands‑on development of deep learning and machine learning models for engineering applications such as electrical/electronic systems, energy systems, data centers, mechanical systems.
• Hands‑on experience on ML/DL models such as time‑series modeling, anomaly detection, root‑cause analysis, diagnostics, prognostics, pattern detection, data mining, etc.
• Programming knowledge – Python, R, Matlab, C/C++, Java, PySpark, SparkR.
• Azure ML Pipeline, Databricks, MLflow.
• Hands‑on optimization techniques like dynamic programming, particle swarm optimization, etc.
• Software development life‑cycle process & tools – Agile development methodologies and concepts including hands‑on with Jira, Bitbucket, and Confluence.
• Knowledge of computer vision, natural language processing, recommendation AI systems.
• Knowledge of traditional and new data analysis methods that can build statistical models and discover patterns in data.
• Knowledge of open‑source projects such as OpenCV, GStreamer, OpenVINO, ONNX, TensorFlow, PyTorch, Caffe, MLOps.
• Knowledge of TensorFlow, Scikit‑Learn, Keras, Spark ML, NumPy, Pandas.
• Knowledge of IoT technologies, including cloud processing such as Azure IoT Hub.
• Knowledge of Scala.
• Excellent verbal and written communication skills including the ability to effectively communicate technical concepts as part of virtual, global teams.
• Ability to understand academic research and apply new data science techniques.
• Experience being part of larger teams with established big data platform practices, as well as smaller teams where they made a bigger impact in terms of scope.
• Experience of working with global teams and strong communication skills to interact with them.
• Self‑directed and hungry to learn – a person who, with time in his/her hands, will independently find interesting ways to push the envelope, learning new skills and growing the self and the team.