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Graduate Technical Intern - Data Scientist

🚀 Off-cycle Internship
💻 Remote
⌛ Closed
Applications are closed

Off-cycle Internship



  • We are a Data Analytics team in SPPD (Silicon Photonics Product Division) responsible for loading Fab / Sort / Test / and Component data into one bare-metal distributed compute and storge platform to provide data analytics solutions to multiple organizations. We build Data Analytics tools (data views, static reports, and interactive applications) in support of the development and manufacturing of PIC (Photonic ICs) including pluggable modules and co packaged optics.


  • Minimum qualifications are required to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
  • Minimum Qualifications:
  • Shall be a student pursuing a Graduate degree (or equivalent) in any of the following or closely related fields:
  • Data Science, Mathematics, Statistics
  • Computer Science, Computer Engineering, Electrical Engineering
  • 1+ year experience with Python
  • Preferred Qualifications:
  • Intermediate to advanced SQL
  • Data processing (ETL and cleaning) using both SQL and a data centric coding language such as R, Python or Scala
  • Quantitative analytics including visual display
  • Dev Ops or Agile experience including CI/CD
  • Experience loading data with Apache Hive or Spark
  • Ability to create interactive applications with Flask or Shiny frameworks

Education requirements

Currently Studying

Area of Responsibilities



  • You will refactor and improve an analytics pipeline and migrate it from a monolithic code base exporting a single flat file, to one with a modular and flexible implementation.
  • You will be responsible for creating the engine for computing quantitative results of comparative performance to support new product introductions. The engine must then save results to the given database.
  • You will either render and save images of quantitative analyses to the database or be able to render the results real time through Python Flask or R Shiny frameworks (preferred) on an existing hosting platform.
  • As a stretch goal, you will utilize Spark ML to rank the most important relationships to improve the usability of the reports.
  • At the conclusion of the internship, you will present your work and provide training to engineers within the Silicon Photonics Product Division


Work type

Full time

Work mode