DAT-014 Data Scientist

Canada-wide Remote

Our Client is building the leading B2B platform for the under-the-radar but massive commercial services industry. Their flagship product, provides rich data on every commercial building in the US (~63M properties) and workflow software to make this data actionable. They’re scaling the team to meet the demands of our growing customer base, ranging from small-medium sized businesses to larger enterprises, such as Siemens and Carrier.

The Data Opportunity

From an engineering perspective, every commercial property means massive data sets – and demanding performance and architecture requirements for your features to be put through. Geospatial data often requires GIS techniques to wrangle datasets – something different than the average SQL join. Data on virtually every commercial property in the US means a chance to see the country by way of satellite imagery, property boundaries, and several hundred other data elements we have already developed.

The data team is at the heart of our business. As a data scientist, your data features frequently close massive deals and drive best-in-class retention. Every customer experiences your improvements immediately – this is not an internal BI role.

Your Role

  • develop new algorithms and models to fuse disjoint data sets to create new analytical insights and intelligence
  • work closely with our data engineering team to write professional code, build predictive analytics and run analytical pipelines
  • wear multiple hats leading different data science projects to improve our data quality and ease of data integration
  • lead the design of our data system and platform architecture
  • be a trailblazer to unlock hidden intelligence/analytics vital to our customers

Qualifications

  • 3+ years experience as a data scientist with production level data scientist and/or software developer
  • Strong fundamentals in data structures and programming languages, such as Python, Scala, R or Ruby
  • Advanced knowledge in SQL and strong data analysis skills, including collecting, analyzing, interpreting and presenting data
  • Experience in building ML models to improve prediction accuracy and drive insights
  • Knowledge and familiarity in leveraging RDBMS (e.g. MySQL, Postres) and NoSQL databases (MongoDB, Cassandra).
  • Ability to communicate requirements and findings to customers and teammates clearly, self-starter and collaborative.
  • A detail-oriented mind with inclination for data investigation

Nice to Have

  • Masters or Ph.D. in Statistics, Mathematics, Computer Science or similar field
  • Experience with distributed Big Data technologies ie. Spark, Scala and Python
  • Experience working with geospatial data
  • Experience in ontologies, knowledge graphs, and graph databases (e.g. AWS Neptune, neo4j)
  • Experience developing and deploying on cloud-based platforms, such as AWS and GCP in a production level, for machine learning
  • Domain knowledge (in prop-tech, CRM platforms, GIS/enterprise workflows, etc)