Is the job funded through the EU Research Framework Programme?
Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?
No
Offer Description
Job Description
Researchers at NUS IORA are working in collaboration with an MNC in the semiconductors industry to use data science and analytics to optimize and streamline their assembly line. We are looking for a full-time Researcher to join our team.
The incumbent will be working alongside a team of data scientists in:
Liaising with the client to come up with use cases where the use of data science can help them streamline their production line and make decisions.
Work hand in hand with the domain knowledge experts from the client side to understand the data and make sense of the analysis being conducted and the results obtained
Setting the path forward, lead the team of data scientists and guide the client in using data science to solve the use cases.
Doing exploratory, predictive and prescriptive analysis of structured data to solve use cases for the client
Transform unstructured data into structured data by building upon or improving the existing data infrastructure for optimal extraction, transformation, and loading of data.
Presenting results of analysis and use cases in a way that can that can be useful for client, to both a technical and non-technical audience
Requirements
Good undergraduate or graduate degree or PhD in a quantitative or scientific field, i.e. STEM background
Comfortable scripting in and performing data analysis in Python or R, and Unix-based systems.
Minimum 3-5 years of experience in conducting statistical analysis (regression, analysis of variance, etc.), text analytics/mining and machine learning (anomaly detection, gradient boosted decision tree, etc.).
Minimum 1-2 years of experience building and optimizing data pipelines, working with different data architectures and data sets, and in using SQL.
Minimum 2-3 years of experience working with companies in client facing roles.
Minimum 2-3 years of experience managing teams doing analytical work or data science.
Requirements Additional Information Where to apply
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