Associate Engineer- Data Science
Eaton
Date: 2 weeks ago
City: Pune, Maharashtra
Contract type: Full time

What You’ll Do
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.
Skills:
Required
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
- Bachelor’s degree in Data Science, Electrical Engineering, Computer Science, Electronics Engineering
- 0-1+ 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
Skills:
Required
- Good Statistical background such as Bayesian networks, hypothesis testing, etc.
- Hands on experinece on ML/DL models such as time series modeling, anomaly detection, root cause analysis, diagnostics, prognostics, pattern detection, data mining, etc.
- Knowelldge on data visualization tools and techniques
- Progamming Knowledge - Python, R, Matlab, C/C++, Java, PySpark, SparkR
- SW Development life-cycle process & tools
- Knowledge on Computer Vision, Natural Language Processing, Recommendation AI Systems
- Knowelldge on traditional and new data analysis methods that can build statistical models and discover patterns in data
- Knowelldge on open source projects like Open CV, Gstreamer, OpenVINO, ONNX, Tensor flow, Pytorch and Caffe
- Knowelldge on Tensor Flow, Scikit, Keras, Spark ML, Numpy, Pandas
- Advanced degree and/or specialization in related descipline (e.g. machine learning)"
- Excellent verbal and written communication skills including the ability to effectively communicate technical concepts as a part of virtual, global teams
- Good interpersonal, negotiation and conflict resolution skills
- 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.
- Innate curiosity
- 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.
- Team player- we work in small, fast moving teams.
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