Senior Data Scientist
Basis:
Permanent - Full Time
Area of Interest:
Data & Analytics
Locations:
Oakville, ON
Design, develop and maintain analytical data products that support the ongoing operational mandates of the ITS Altitude platform. Deliverables may include, but are not limited to, application programming interfaces (API), data pipelines (end-to-end data processing), product analytics, geospatial reference data, predictive models and customer defined data sets.
Collaborate with research teams to operationalize research data sets into geospatial data products that support ITS Altitude objectives.
Implement new statistical or mathematical methodologies for specific models of data analysis.
Provide expert project leadership as a SME: guidance to team members and participate in cross-departmental projects establishing Geotab as a leader in data science.
Create algorithms and models to extract information required to solve complex business problems.
Conduct causality experiments by applying A/B experiments or epidemiological approach to identify the root issues of an observed result.
Identify new, complex queries from Big Data infrastructure from data warehousing database (i.e. Google BigQuery) to add value to the organization.
Use machine learning (ML) packages (e.g. Scikit-learn and Tensorflow) to develop ML models and features.
Test the performance of data-driven products and make recommendations for improving ITS Altitude’s product suite.
Ongoing maintenance and support of existing data-driven products to drive improvement and identify opportunities for enhancements.
Post-secondary Diploma/Degree specialization in Data Science, Mathematics, Computer Science, Statistics, or related field.
Graduate or post-graduate Degree in Data Science, Mathematics, Computer Science, Statistics, or a related field is highly valued.
5-8 years of experience as a Data Scientist or similar role.
5-8 years experience in writing SQL queries.
5-8 years experience in programming in Python.
Solid understanding of machine learning and operations research.
Knowledge of data management and visualization techniques.
Affinity for statistical analysis and predictive modeling.
Experience in the transportation industry and/or with intelligent transportation systems is highly valued.
Experience in geospatial modeling and analysis is an asset.
Experience with data-as-a-service architecture and cloud-based technologies is an asset.