Engineer - Data Science

Eaton; Maharashtra; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Eaton Corporation’s Center for Intelligent Power is seeking a Data Scientist to design and develop ML/AI algorithms for power management, and to integrate them into edge or cloud systems through CI/CD and software release processes.

The role requires collaboration with experts in deep learning, ML, data engineering, and product teams to deliver end-to-end pipelines and scalable intelligent power solutions across complex engineering systems.

Qualifications

• Master’s degree in Data Science or related field.
• 2+ years delivering technology solutions in production environments.
• 2+ years applying statistics, ML/AI to solve business problems.
• 2 years working with customers as a solutions architect.

Responsibilities

• Design and develop ML/AI algorithms for power management.
• Integrate algorithms in edge or cloud systems using CI/CD and software release processes.
• Deliver projects with strong architecture, technical deliverables, and on-time delivery.
• Collaborate with deep learning, ML, data engineering, and product teams.
• Develop end-to-end pipelines and end-to-end intelligent power solutions.

Skills

Bayesian networks

Deep learning

Time series

Anomaly detection

Root cause analysis

Diagnostics

Prognostics

Pattern detection

Data mining

Python

R

Matlab

C/C++

Java

PySpark

SparkR

Azure ML Pipeline

Databricks

MLFlow

Dynamic programming

Particle swarm optimization

Jira

Bitbucket

Confluence

Computer Vision

NLP

Recommendation AI

OpenCV

Gstreamer

OpenVINO

ONNX

TensorFlow

PyTorch

Caffe

MLOps

Scikit-learn

Keras

Spark ML

Numpy

Pandas

IoT

Azure IoT Hub

Scala

Education

Master’s Degree in Data Science

Tools

Jira

Bitbucket

Confluence

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 like electrical/electronic systems, energy systems, data centers, mechanical systems
• Hands on experinece on ML/DL models such as time series modeling, anomaly detection, root cause analysis, diagnostics, prognostics, pattern detection, data mining, etc.
• Progamming 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.
• SW Development life‑cycle process & tools Agile development methodologies and concepts including handson with Jira, bitbucket and confluence.
• Knowledge on Computer Vision, Natural Language Processing, Recommendation AI Systems
• Knowledge on traditional and new data analysis methods that can build statistical models and discover patterns in data
• Knowledge on open source projects like Open CV, Gstreamer, OpenVINO, ONNX, Tensor flow, Pytorch and Caffe, MLOps Knowledge
• Knowledge on Tensor Flow, Scikit, Keras, Spark ML, Numpy, Pandas
• Knowledge of IoT technologies, including cloud processing, like Azure IoT Hub.
• Knowledge of Scala
• Excellent verbal and written communication skills including the ability to effectively communicate technical concepts as a part of virtual, global teams
• Ablity 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 working with global teams and strong communication skills.
• 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 Self and the team.