Data Science Competition

Data Science Competition

Challenging students to engage with data

How Data Science competitions work

Step 1

Various organizations provide a project and dataset for students

Step 2

Students work in groups of and submit their analysis before the deadline

Step 3

Submissions are ranked and the top submissions are invited to present their results

Step 4

The best presentations are awarded the prizes

Upcoming competitions

November 17 to November 27 2016



Data Science is becoming an increasingly important field. At the forefront of data science, cutting edge machine learning is revolutionizing all aspects of technology, business, and life.

DataSense and Microsoft are co-hosting this case competition to help you understand the use of Azure machine learning platform for data analysis and provide you with valuable experience dealing with real data.

The info sessions concerning an introduction to Azure machine learning will be held by Microsoft on November 17. You can start working on the case with a team after the info session. The top teams are invited to present their analysis live in front of a panel of judges. (A Microsoft recruiter will be there!)

We encourage students (undergraduate or graduate) from all faculties and departments come together to analyze a dataset and apply machine learning to generate insights.

Even if you aren’t planning on competing, you are still invited to attend the info session to learn the Azure machine learning

The Challenge

In Canada, there is a wide range of households, occupations, and jobs. As students, perhaps thing we care most about is salary - how much money can I expect to make when I graduate? Will university even help me earn a higher salary?

To answer these questions in today's world of data, we challenge you to build a machine learning algorithm which "learns" patterns from real world data to predict how much money you will make. You will learn the basics of machine learning, and apply it to discover insights from the Canadian Census. You can even use your model to predict your own salary!


  • November 17th - We will be announcing the details of the competition along with a Machine Learning workshop to help you get started.
  • November 28th - Submissions due online (details TBA)
  • Date TBA - Invited presentations by the top teams and live judging

For specific times and locations, please refer to our facebook page here:


To be announced!

Microsoft Machine Learning Competition - Predicting Salaries

Select your tickets

Description Price Quantity

General Admission



DataSense Members



Past competitions

March 3 to March 17 2016
UN-logo bdu-logo quandl-logo mobify-logo


“Big Data Big Impact” (organized by DataSense, IONA Journal of Economics, and IBM's Big Data University) aims to bring participants a one week, cross-disciplinary event focused on using data science to evaluate one of the United Nations Sustainable Development Goals. Everybody is welcome to participate (that means current students, alumni, etc from any University in Vancouver such as UBC, SFU, etc). { Goal: Sustainable Development Goal 08: “Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all.” { Challenge: Participants will compete in cross-disciplinary teams of 3-4 people from a range of fields including Economics, Finance, Computer Science, Statistics, Mathematics, etc. The competition is open to anybody interested in statistical programming and its economic application. Check out our slides from our info session here for details on what you're expected to do: { Judging: The top teams will be invited to our live judging session. Our judging panel will consist of professionals (IBM, Mobify) and professors. Check out our facebook page for the latest profiles of our judges!


  • March 3rd // Optional info-session, team forming, and Data Science Bootcamp - slides are here if you missed the session:
  • March 7th // Followup Q&A session + time to work (with free food!) - register at
  • March 13th // Submissions Due Online (details TBA)
  • March 17th // Invited presentations by the top teams and live judging
For specific times and locations, please refer to our facebook page here:


1st Place - Undergraduate Team
*Each undergraduate team must include only consists of participants either currently in a Bachelor's program. Participants who have finished their bachelor's degree and/or started a graduate degree are not eligible. Teams may range from 3-4 students.
Teams will receive the opportunity to publish their data presentation in the Spring 2016 Volume I of the UBC IONA Journal of Economics (printed and online), copies of Advanced Analytics with Spark for all team members (provided by Big Data University), as well as ONE of the following two prize packages from our partners:
  • Quandl Prize Package - featured blog post on and interview for internship
  • IBM Big Data University - featured blog post on
1st Place - Open Category
*There are no restrictions on teams competing in this category
Teams will receive copies of Advanced Analytics with Spark for all team members (provided by Big Data University) and be able to select in ONE of the following two prize packages from our partners:


November 17 to 23, 2015



In anticipation of SportsHack, DataSense and Big Data University are co-hosting a pre-competition to get in the mindset of analyzing data. Your mission, should you choose to accept it, is to analyze a dataset from the City of Vancouver so that we can learn more about our great city. We challenge you (in groups of 2 or 3) to explore the data and find interesting stories.
The Data is now released and the competition has now begun! We encourage you to "get your hands dirty" and compete! You are also invited to attend the finals, where the top 8 teams will give a 5 minute talk about their results.

The Data

Learn more about your task with the slides from our info session:
Check out the dataset here:
Questions? Send an email


Recruiters/hiring managers will be ON-SITE during the 5 minute presentations! If you're looking to make an impression, and are hoping for a career in Data Science, this is your chance!