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5700 Yonge St, North York, ON M2N 5M9, Canada

Position Overview Senior Data Scientist – Growth Portfolio (QFG). The role focuses on building and maintaining the data value chain for alternative investments, including crypto, derivatives and precious metals, leveraging BigQuery, Looker, Python and GKE. The engineer will accelerate compliance reporting, dashboards and self‑serve analytics, and drive AI‑driven automation to support business strategy and operational effectiveness.

Key Responsibilities

Reporting & compliance foundation: Build and operate daily reconciliation and supervision/surveillance reporting flows for crypto, derivatives and precious metals products; ensure outputs are reliable, traceable and delivered via approved secure mechanisms.

Data integration & modeling: Ingest, model and curate core datasets in BigQuery; define metric definitions with clear grains and ownership.

Dashboards & monitoring: Execute full lifecycle from data pipeline to shipped dashboard, choosing the right tool (Looker, Grafana, PyShiny, etc.).

Self‑serve enablement: Build and maintain queryable tables/views, documentation, interfaces and examples so internal users can answer questions, explore data and generate insights.

Production engineering & delivery: Write and ship production code; collaborate on shared codebases with software engineers; deploy through CI/CD pipelines and monitor services on scalable infrastructure (GKE/Kubernetes).

Stakeholder partnership & problem solving: Engage directly with compliance, ops, product and business leaders; diagnose issues and deliver solutions.

Automation & AI that compounds: Automate recurring workflows, shrink manual operational load, use AI to draft pipelines, generate tests, explore data faster and prototype solutions.

Stack pragmatism:



Work with BigQuery + Looker + Python microservices in GKE; shape direction if better ways exist while pragmatically working with legacy systems.

Qualifications

Strong SQL and Python; track record owning production data pipelines and analytics outputs end‑to‑end.

Experience with modern cloud data analytics platforms (GCP BigQuery, Databricks, Snowflake, etc.).

Strong data modeling instincts and ability to create stable metric definitions.

Experience building dashboards that people actually use and evolving them with the business.

Production software engineering: write code that ships; collaborate on codebases via Git; comfortable with CI/CD and container orchestration (Docker, Kubernetes/GKE).

Comfort operating in regulated environments with strong privacy/PII awareness and auditability discipline.

Exceptional written and verbal communication skills; translate data speak into business decisions.

High autonomy: prioritize, ship thin slices and navigate enterprise constraints without stalling.

AI‑first mindset; concrete examples of using AI to accelerate engineering/analytics work, automate repetitive tasks and continuously improve workflow.

Product analytics instrumentation/experimentation (e.g., Amplitude).

Time‑series forecasting or operational modelling.

Experience with GCP data services beyond BigQuery (Dataflow, Composer/Airflow, Pub/Sub) or equivalent AWS/Azure suite.

Success enabling self‑serve analytics / data democratization in complex organizations.

Enterprise or hobby projects building LLM applications with an Agent Framework (LangChain, LangGraph, etc.) – bonus.

Compensation Base salary range: $130,000 – $170,000. Final package includes a comprehensive perks plan and a competitive incentive (bonus) program for full‑time permanent roles.

EEO Statement At Questrade Financial Group of Companies, we are committed to fostering a diverse, inclusive and accessible work workplace where individuals are treated with dignity and respect.

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Apply on Kit Job: kitjob.ca/job/2g91xl

📌 Principal Data Scientist (Toronto)
🏢 Questrade Financial Group
📍 Toronto