Eaton

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 algoriths, 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 of working with global teams work Experience and awareness, Strong communication skills to interact with global teams.
* 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.

Data Science

Data

Algorithm

Machine Learning

Project management

Agile

Cloud

Data analytics

Software Development

Deep Learning

Continuous Integration

Analysis

Azure

Testing

Python

Java

Program Management

Data Engineering

NumPy

Computer Vision

Pandas

Scala

Communications

MATLAB

Electrical Engineering

Statistics

Apache Spark

Jira

PyTorch

Keras

Research

Big Data

Azure ML

Databricks

MLflow

Recommendation systems

TensorFlow

Scikit-learn

Engineer - Data Science