Data Scientist at Tucows Inc. (Toronto, ON, Canada)

Data Scientist at Tucows Inc. (Toronto, ON, Canada)

Tucows is looking to add two Data Scientists to our Analytics & Insights team. Together, we’re responsible for all of the reporting, analytics, data flows, visualization, machine learning and related business intelligence operations within the company.  

Success in this role requires four related components.  The first is that at your core, you are curious.  You live for going down the rabbit hole. Chasing mysteries, finding quirks, and peeling back all the layers.  Finding new questions to you is almost as fun as answering them, but answer them you do, with solid statistical proof displayed in clear language and compelling visualizations.

The second requirement is an ability and interest in understanding our business.   We’ve got lots of data, but it’s not going to turn itself into information, and you can’t help with that unless you understand what the numbers mean.  Learning about our business will be made both easy and fun by your deep and passionate love of the internet.  You believe it’s powerfully transformative and even, perhaps, the greatest thing ever.  You can’t wait to be a part of helping Tucows make the internet even more awesome.

The third component is that you really, for serious­, love math and coding. Your arsenal of algorithms is both deep and broad.  You know precisely which tool is right for the job and you also know why.

The last, but certainly not least, component is the ability and willingness to continuously learn about new technologies. The data science ecosystem is a fast-evolving beast. Newer and more powerful tools are released all the time. You are a data scientist who is constantly updating their knowledge of data science state-of-the-art.

If you have these four qualities, you’ll find Tucows an exciting, ambitious and supportive environment in which to do impactful data science work.  

Main purpose of position:

Responsible for the provision of information to drive business decision making, via:

  • Ongoing collaboration with business specialists to understand drivers and needs
  • Analysis of our unique data sets, including:
    • Sales and usage data
    • Web and social analytics
    • Unstructured text  
    • Forecasting and time series data analytics

  • Leveraging existing data sets to provide predictive information
  • Ongoing evaluation of available structured and unstructured data sets
  • Experimentation with data to find useful insights
  • Application of machine learning (regression, clustering, classification, deep learning etc) processes and techniques
  • Application of natural language processing techniques and tools

Key position responsibilities/objectives:

% of Time | Description of task/duty

25% | Responsible for cooperative ongoing dialogue on business requirements for information

50% | Responsible for self-directed research into available data sets and the various possibilities for extracting information relevant to the business, and for engagement of business functions in the evaluation of results

15% | Responsible for evolution of tools and techniques for the extraction and delivery of information and insights to internal and external customers

10% | Responsible for documentation of processes for converting data into information, and training/assistance for internal resources on how best to utilize the resulting reports etc.

Knowledge, Skills & Abilities

  • Top-notch communication (verbal and written) and interpersonal skills
  • Excellent math and statistical analysis skills, especially as they pertain to business and experimentation
  • Deep knowledge and experience of the algorithms and techniques of modern data science
  • An interest and proficiency in the presentation and visualization of numbers and statistical data
  • Ability to understand business imperatives and drivers, find relevant data correlations, and create processes by which the data correlations are translated to information flows that help drive the business
  • 3-5 years of quantitative analysis experience, including handling, manipulating and analyzing data and creating analytical reports
  • Knowledge and experience of semantic and sentiment analysis, machine learning, and natural language processing
  • Comfortable writing complex SQL queries to extract and integrate data from multiple database sources
  • Comfortable using programming languages such as Python and/or R to work with data sets
  • Excellent knowledge of Microsoft Excel and Google Docs
  • Ability to document work and effectively prioritize documentation
  • Ability to work on multiple projects in parallel while managing constantly changing deadlines and priorities

Nice to haves:

  • Experience with Hadoop, Spark and similar data storage and processing tools
  • Experience with deep learning methodologies
  • M.S. or Ph.D., preferably in a statistical, mathematical, or technical field

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