Global Tech Sales Researcher (Part-Time)

Champaign, Illinois, United States Part-time


We are looking for someone who can tap into their deep knowledge of data analytics to create robust data pipelines that will scale to our global markets. Each member of our team is passionate about leveraging data analytics to discover invaluable insights from our extensive global sales data. We have a broad skill set and are willing to take on any challenge. We look for someone who embraces our passion for beer and building things from scratch. Bud Lab harbors a start-up environment with all the resources and future opportunities of a large corporation.


Here at Bud Lab, we value a great fit with our culture and we seek people from diverse backgrounds. Past members of this team have varied from masters students in statistics to PhD candidates in plasma engineering. You should be able to quickly communicate with SQL databases to grab datasets. You should also be equipped to write efficient scripts to clean, explore and visualize these datasets (preferably in Python). Your duties will include developing new as well as existing data analytics tools that we build here at Bud Lab for several business regions around the world.


Purpose of Role / Responsibilities:

  • Development of advanced analytics algorithms and tools to facilitate research and capabilities for the Global Tech Sales team.
  • Leverage research methodologies efficiently to create data pipelines that extract valuable insights from our global sales data.
  • Grab datasets from servers, efficiently plot, explore and preprocess to discover patterns in sales, social media or geographic information about beer suppliers.
  • Collaborate in a team of graduate-level researchers in the Bud Lab 
to deliver innovative solutions to teams located around the world.


  • Master's or PhD in Statistics, Mathematics, Computer Science/Engineering, Economics or related analytics field preferred.

Mandatory Requirements:

2+ years’ experience in programming in a quantitative analytics setting
  • Experience with SQL, Python, R/MATLAB, C++ or Java
  • Experience manipulating large technical data sets
  • Experience in clustering analysis, modeling, regression-based analysis or machine learning in general
  • Familiarity with data science libraries in at least one language
  • Strong communication skills

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