Abbott Laboratories

Data Scientist (Based in Tuas)

Job description

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

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