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Data Science Intern

Edinburgh, Great Britain & Northern Ireland, United Kingdom
Jan 18, 2021


Job Description


At Xilinx, we are leading the industry transformation to build an adaptable, intelligent world. Are you bold, collaborative, and creative? At Xilinx, we hire and develop leaders and innovators who want to revolutionize the world of technology.  We believe that by embracing diverse ideas, pushing boundaries, and working together, anything is possible.

Our culture of innovation began with the invention of the Field Programmable Gate Array (FPGA). The introduction of our Adaptive Compute Acceleration Platform (ACAP) has made a quantum leap in capability, solidifying our role as the adaptable platform supplier of choice.  From the start, we have always believed in providing inventors with products and platforms that are infinitely adaptable. From self-driving cars, to world-record genome processing, to AI and big data, to new 5G networks, we empower the world’s builders and visionaries whose ideas solve every day problems and enhance people’s lives.

If you are PASSIONATE, ADAPTABLE, and INNOVATIVE, Xilinx is the right place for you!  At Xilinx we care deeply about creating meaningful development experiences while building a strong sense of belonging and connection. We foster an environment of empowered learning, wellness, community engagement, and recognition, so you can focus on work that matters – world class technology that improves the way we live and work.

This position is a 3 to 6 Month internship for a student currently pursuing studies in a Data Science related subject. You will be working closely with an experienced design team, developing scripts and reporting mechanisms to extract value from the data produced by the design team. You will need a strong interest in multi-variate analysis, data cleaning/munging and visualisation/reporting. You will learn how to apply data science concepts to a highly specialised field, necessitating frequent discussions with subject matter experts.



  • Programming & Scripting Skills – Perl / Python
  • Experience in using Linux
  • Data-driven problem solving & Exploratory Data Analysis
  • Data Cleaning/Munging techniques, extract information from a variety of potentially messy data sources.
  • Data Visualization & Communication, ability to describe your findings and methods
  • Good understanding of statistics, and the dangers of misrepresentation / overfitting


  • Knowledge of Dimensionality reduction / Pruning techniques and Principal Component Analysis, Decision Tree Techniques / CART
  • Knowledge of Models and Techniques for Root Cause Analysis
  • Hypothesis testing – Likelihood-ratio / Wald test


Education Requirements

  • Currently completing an undergraduate degree in Computer Science, Data Science, Software Engineering or equivalent.

Years of Experience

Refer to the Talent Network

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