We’re growing and looking to add a Data Scientist to our Engineering team in British Columbia, Canada or Texas, USA.Where would this person be located? Great question! It started remotely and we try to hire remotely when we can. We are open to hiring this Data Scientist remote in British Columbia, Canada or Texas. However, we do have offices in Austin, TX, Vancouver, BC and Shenzhen, China now (yay!). So if you are located in Vancouver or Austin - we would love to have you join our office!

        Interested in helping us innovate and build industry-leading data-driven products for our customers? Let’s get into the details:

What you'll do:

• Work with stakeholders throughout the company to source opportunities for creating data-driven products


• Regularly present and communicate insights to stakeholders


• Extract mission-critical insights from datasets


• Create scalable models that drive business decisions and enable our customers’ success


• Develop tools to monitor models for evolving performance and accuracy

If your answer is “heck yeah!”, please read on….

Who you are:

• Masters (Ph.D preferred) or an extensive background in analytical work


• Familiarity with writing high-quality Python code


• Exposure to machine learning tools and frameworks such as, but not limited to Pandas, scikit-learn, NumPy and SciPy


• Experience solving nebulous problems using a systematic, analytical approach


• Strong command of SQL and working with multiple relational databases and data warehouses (Redshift, Snowflake, Postgres, MySQL, etc…)


• Ability to be scrappy with extracting useful insights with partial data


• Ability to apply modeling techniques and machine learning methods (Bayesian statistics, OLS regression, GLMs, logistic regression, network analysis, clustering, decision trees/random forest, dimensionality reduction, neural networks, etc...)


• Able to communicate insights through visualizations using libraries such as matplotlib, seaborn, plotly, etc…


• Approach problems with a customer-centric lens

Bonus points:

• Some experience with analyzing time-series data


• Familiarity with analyzing big datasets using tools such as Apache Spark


• Some experience with R and related machine learning libraries


• Additional experience with deep learning frameworks such as TensorFlow and PyTorch


• Experience with accessing data from other datastores in the AWS ecosystem such as ElasticSearch, S3, and DynamoDB


• Exposure to working with software development teams and using tools such as Git, GitHub, and Zenhub