Data Scientist – Hybrid, Toronto

About the role

We are seeking a skilled Data Scientist to join a leading financial institution in Toronto on a 6‑month contract. The role focuses on building and delivering machine‑learning and AI solutions that support customer and advisor analytics across multiple banking verticals.

Key responsibilities

• Prepare, clean, and analyze complex internal datasets to generate ML/AI features.
• Leverage large language models (LLMs) to extract features from unstructured data.
• Design and build segmentation and predictive models for customer and advisor analytics.
• Own the feature‑engineering pipeline for ML/AI models.
• Collaborate with business stakeholders to define data requirements and performance metrics.
• Create dashboards and reporting assets to deliver insights.
• Contribute to the development of generative AI components such as RAG systems and NL‑to‑SQL workflows.
• Document data sources and support continuous‑improvement tracking.

Required profile

• Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering or related field.
• 3‑5 years of technical experience in data science or analytics.
• Strong ability to translate ambiguous business questions into structured analytical approaches.
• Curiosity about GenAI and willingness to learn LLM‑related workflows.

Required skills

• Python (pandas, NumPy, scikit‑learn, PySpark or similar).
• SQL and data‑modeling concepts.
• BI tools such as Power BI or Tableau.

What we offer

• Hybrid work arrangement (onsite and remote).
• Competitive hourly rate starting at $64 CAD.
• Opportunity to work on cutting‑edge AI projects within a major financial institution.