Data Science Intern - Remote

$25.00 hourly
  • CafeMedia
  • Remote
  • Sep 03, 2020
Intern Data Science

Job Description

CafeMedia helps over 2,500 online creators make a living doing what they love – producing great content – while we manage the advertising for them. Through our remote internship program, we want to help students gain real-world experience in digital media, online advertising, and technology, and develop a shared passion for a creator-first future of the open web. We are deeply committed to being leaders in our industry in regards to diversity, at all levels, and would love to hear from great candidates of all backgrounds.

We are looking for a part-time Data Science Intern for the Fall of 2020, 16-20 hours per week. They will assist in the development of CafeMedia’s yield strategy and audience capabilities, rolling up their sleeves to collect, organize, segment, and analyze data. This is an excellent opportunity for someone passionate about big data.

Role & Responsibilities:

  • Develop and maintain classification and clustering models using machine learning
  • Expand our business intelligence and model outcome reporting
  • Document analytical processes
  • Improve data visualizations for end users

Skills and Competencies:

  • Working on M.S. or PhD in Computer Science, Statistics, Industrial Systems Engineering (ISE) or a related discipline
  • Familiarity working with large-scale systems and data platforms (e.g. Hive, AWS, BigQuery,
  • Snowflake)
  • Familiarity using a scripting language (e.g. Bash, Python, Perl)
  • Familiarity using a statistical analysis language (e.g. R, SciPy)
  • Exposure to in data mining, machine learning, predictive analysis and NLP (Natural Language
  • Processing) preferred
  • Excellent analytical skills to deliver meaningful and impact-driven insights

CafeMedia is committed to diversity, equity, and inclusion. We believe we are most impactful when people with a wide range of backgrounds, experiences, and identities come together with common purpose. We encourage candidates from all backgrounds to apply.