Data Scientist (Based in Tuas)

Responsibilities:

• Analyze manufacturing data, draw insights, and present results in a cohesive, intuitive, and simplistic manner
• Utilize technologies to collect, clean, analyze, predict, and effectively communicate information
• Prepare both structured and unstructured data for analysis
• Able to examine data sets and determine the best end-to-end analysis plan to address key business questions and create value
• Conduct advanced statistical analysis to determine trends and significant data relationships
• Develop machine learning models to apply test data algorithms to future data
• Validate models/analytical techniques, and develop algorithms to execute analytical functions
• Works with stakeholders to define business questions, requirements, timelines, objectives, and success criteria to address need.
• Proactively identifies opportunities for significant operational, process or system level product improvements.
• Communicate model logic and restrictions
• Work closely with the business to understand the domain and iteratively refine analyses
• Transform analytical results into actionable recommendations for business partners using deep industry knowledge
• Translates manufacturing data into actionable insight that can be used to increase manufacturing capacity, efficiency and achieve quality objectives
• Provides input into developing departmental and site processes and procedures.
• Guide and otherwise contribute to technical teams in development, deployment and application of applied analytics, predictive analytics, prescriptive analytics, etc.

Requirements:

• Bachelor's Degree in Computer Science, Data Analytics, Mathematics, Statistics or similar/related disciplines
• 3-7 years of related work experience, preferably with some experience in Manufacturing Analytics
• Advanced Experience with programming scripts such as Python, Java, Scala, C++ in Linux/Unix, and R
• Experience in applying data analysis techniques to large data sets
• Advanced analytics knowledge and application in the field of Statistics, Mathematical programming
• Strong business acumen and experience with operational or strategic systems