Data Scientist

at ShareDesk in Vancouver

ShareDesk is looking for an experienced Data Scientist to help us analyze user data and create algorithms to provide context to our mobile and web-based products.

We are capturing lots of data on how people use workspace. To make our products truly ‘smart,’ we need you to normalize data, spot trends, and write code which we can use to add layers of logic.

This is an opportunity to work with a small, dedicated team of developers, where you’ll be asked to take a significant amount of personal responsibility for the code you ship. It means you’ll make decisions that have a direct impact on our business, every day.

We’re looking for enthusiasts, people eager to be a part of a company that seeks to evolve the way people work. Candidates who can demonstrate passion, both for their individual contributions and for being an integrated part of our team, will win us over.


Use statistical methods in a business environment with measurable results (i.e. predictive modeling, customer profile and segmentation, and marketing mix modeling)

- Pull data and conduct product analysis to discover and suggest new product functionality and optimize existing services and systems.
- Work with existing data to predict outcomes when one variable is changed
- Write methods using data to influence decision making.


- A graduate degree or equivalent in applied statistics, computer science or a quantitative domain
- At least 3 years working professionally in a data science position
- Strong background in Statistics, Math, Data Mining and Machine Learning Algorithms
Strong R, Python or similar skills
- Intermediate to expert proficiency with SQL
- Ability to listen, learn, share and contribute

Great to haves

- Experience with web-based data analysis. (i.e. A/B testing for web)
- Knowledge of enterprise-level requirements and security concerns
- Understanding of Linux and Git a plus
- Experience with data visualization tools, such as D3.js, GGplot, etc.

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Published at 22 Jul 2016
Expires on 22 Jan 2017
Viewed: 1308 times

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