
Data Scientist – Information Technology
- Canada
- Permanent
- Full-time
- Participate in problem solving initiatives, collaborating within a cross functional team of specialists, to design innovative solutions for clients and business leaders.
- Participate in the wrangling of data, especially regarding the more practical aspects like quality assurance, cleaning, aggregation and integration.
- Apply data science expertise including descriptive, predictive, machine learning, deep learning, and AI techniques to generate new insights and solve business problems.
- Demonstrate creative problem solving and ability to translate data patterns into business insights, cause/effect relationships and variables to amplify predictive power of underlying models.
- Provide business recommendations by distilling complex data science findings into clear, actionable insights, and effectively presenting them through visual displays to stakeholders at all levels, assisting with data-driven decision-making.
- Bachelor’s, Master’s or Doctoral degree in computing science, statistics, mathematics, engineering, or a related field in which advanced statistical methods are used.
- 5+ years of quantitative analysis experience, including handling, manipulating, and analyzing data and creating analytical reports.
- Ability to translate business questions to data questions and present results in ways that make complicated relationships clear.
- Comfortable using one or more statistical programming languages (i.e., Python/R) for data analysis and data engineering languages such as SQL and PySpark to work with large data sets and relational databases.
- Familiarity with Azure, Databricks, Power BI and star schema data modeling is preferred.
- Strong written and verbal communication skills.
- Ability to work effectively as an autonomous data scientist on a small project, and to collaborate with an interdisciplinary group on larger projects.
- Disciplined curiosity, consistent with the best traditions of science.
- Deep knowledge and experience of the algorithms and techniques of traditional statistics and modern data science especially as they pertain to business and experimentation.
- Experience in utilizing Generative AI to solve business problems with unstructured data, with the focus on enhancing efficiency, fostering innovation, and driving organizational impact.