Entry Level Data Analyst jobs in Canada

Position Title: Distribution Data Scientist – Jr.
Est. Start Date: ASAP
Duration: 12 months
Possibility of extension: Yes

A specialist position that combines knowledge of financial markets and investment sales with data and technology skills. Uses advanced analytical algorithms and technologies (e.g. machine learning, deep learning, artificial intelligence) to mine and analyze large sets of structured and unstructured data to obtain insights. Designs and constructs new processes for modelling data. Develops predictive models and leverages data technology to design solutions that deliver smarter business decisions. The ideal candidate will be collaborative and sociable, and will work with data engineers to set up analytics, as well as investment distribution teams to implement analytics solutions.

1. Uses machine learning methods to create and test new sales strategies for investment distribution teams.
2. Works with data engineers and business analysts to create data pipelines and analytics tables.
3. Uses data mining and extracts usable data from valuable data sources to assess feasibility of AI/ML solutions for improved processing and usage of organizational data.
4. Conducts large-scale analysis of information to discover patterns and trends by combining different modules and algorithms.
5. Uses analysis to provide recommendations and advice for business leaders to maintain market competitiveness.
6. Develops prediction systems and machine learning algorithms. Investigates additional technologies and tools for developing innovative data solutions for business stakeholders.
7. Communicates abstract concepts in simple terms.
8. Fosters strong internal and external networks and works with and across multiple teams to achieve business objectives.
9. Anticipates trends and responds by implementing appropriate changes.
10. Broader work or accountability may be assigned as needed.

1. 5+ years of relevant experience and/or certification in related field of study or an equivalent combination of education and experience. CFA or advanced degree in relevant field preferred.
2. SQL, Python/R/SAS, and visualization (e.g., PowerBI) skills are essential.
3. Data analytics and machine learning skills are essential.
4. Collaboration & team skills, with a focus on cross-group collaboration.
5. Ideal candidates will be personable with strong written/verbal communication skills in addition to technical skills.
6. Able to manage ambiguity.
7. Data-driven decision making.
8. Seasoned expert with extensive industry knowledge.
9. Knowledge and experience in the investment industry or financial sales is a major asset.