Dow Productivity Engineer Vacancy – Chemical Engineering Apply


Dow Productivity Engineer Vacancy - Chemical Engineering Apply

Dow Productivity Engineer Vacancy – Chemical Engineering Apply

Dow hiring chemical engineering candidates. Productivity & Analytics Engineer vacancy. Chemical engineering job opening 2022. Dow announces job opening for chemical engineering candidates. Candidates with bachelor’s and master’s degree in chemical engineering may apply for the job opening at Dow for the post of Analytics Engineer. Check out all the details on the same below:

Job Title: Productivity & Analytics Engineer

Primary location Chennai (IND), India

Job Number: R2034053

Eligibility Criteria:

  • Bachelors/Masters of Science in Chemical Engineering from reputed Indian Institutes
  • Background in scripting languages (VBA), either through coursework or projects
  • Solid data analysis skills, and knowledge of statistical and analytics software such as Python, R, JMP, Tableau, Power Bi, etc

Experience:

3-5 years’ Experience in areas such as Chemical or petrochemical manufacturing, maintenance, application of LEAN principles, advanced data analytics/modeling

Key Responsibilities:

  • Lead and execute key productivity improvement projects
  • Performs advanced data mining & analytics on all productivity and reliability data to identify opportunities to further improve waste elimination and improve how work is performed.
  • Leads or participates in efforts to define additional productivity data needed to identify & eliminate waste and in the subsequent efforts to develop and improve electronic tools and systems for said purpose
  • Establishing and maintaining key metrics focusing on leading indicators to improve reliability
  • Work with individual zone reliability engineers to execute the improve reliability work process, including maintaining the site reliability metrics (Reliability, Turnaround, Productivity, etc).
  • Develops processes to utilize other data sources to validate & improve planning standards
  • Develops management reports on productivity based on advanced data mining & analytics
  • Support site teams and networks using LEAN fundamentals: Maintenance Group Leaders Team, Planner Networks (Daily & Turnaround), Work Coordinator Network and Scheduler Networks, Reliability Engineer Network, Production Planning
  • Explore the latest technologies in data mining and modeling, and their applications in the context of maintenance and reliability projects

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