Data Analyst

Location: Toronto, ON

Onsite Flexibility: Hybrid - 4 days on site

Contract Details

- Position Type: Contract
- Contract Duration: 12 months (extension possible based on business needs and performance; conversion possible based on business needs and performance)
- Pay Rate: C$44.00-C$53.00 / Hour (CAD)
- Shift / Schedule: Monday-Friday, 9:00 AM - 5:00 PM
- Travel Requirements: Not required

Job Summary

The Data Analyst will design and deliver end-to-end analytics solutions combining data science, advanced analytics, and business intelligence. This role applies statistical analysis, machine learning, and data-driven experimentation to solve complex business problems, while also translating these insights into scalable dashboards, reporting solutions, and decision-support tools for stakeholders. Success in this role requires strong depth in data science and analytical problem solving, complemented by the ability to deliver intuitive, business-facing BI solutions that drive adoption and impact. This is an AI project with heavy focus on knowledge of reporting, situated within a collaborative team of seven, including six data scientists and one BI specialist, with a two-week training period at the outset.

Key Responsibilities

- Apply statistical analysis, machine learning, and advanced analytics techniques to identify trends, risks, and optimization opportunities
- Design and build analytical models, experimentation frameworks, and data-driven solutions to address complex business problems
- Develop and maintain curated datasets, feature layers, and analytical data models to support both modeling and reporting use cases




- Translate ambiguous business problems into structured analytical approaches, KPIs, and measurable outcomes
- Deliver insights through interactive dashboards (Power BI), reporting solutions, and executive-ready storytelling
- Partner with stakeholders to define analytical requirements and design data-driven decision frameworks
- Ensure data quality, validation, and governance across both analytical models and BI outputs
- Operationalize analytics through automated pipelines, monitoring solutions, and repeatable reporting processes
- Continuously improve analytical methodologies, data assets, and reporting efficiency
- Support risk and control objectives through analytical monitoring and insight generation

Must-Have Requirements

- Proficiency in Python (including Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, and PySpark).
- SQL- writing complex queries, stored procedures, and data extraction.
- Experience with cloud-based data and AI/ML platforms (e.g., Azure, AWS, or GCP), including deploying and managing models in production environments.
- Proficiency in Power BI to create impactful visualizations and dashboards

Required Skills

- Strong organizational skills with the ability to work in a fast-paced environment and manage multiple deadlines and priorities




- Ability to effectively work in teams across the bank with multiple stakeholders and to influence and align others
- Strong risk acumen - challenges the status quo and proactively manages risks
- Ability to work in ambiguity and simplify complex issues
- Robust work ethic and ability to execute with speed

Preferred Skills

- Proficiency in Tableau
- Hands-on experience with machine learning techniques, including supervised and unsupervised learning, reinforcement learning, and causal inference
- Experience building, training, and deploying machine learning models, including model pipelines, feature engineering, hyperparameter tuning, and model explainability

Education Requirements

- Undergraduate degree or advanced technical degree preferred (e.g., mathematics, physics, engineering, finance, or computer science)
- No certifications required

Required Experience

- 5-7 years of overall experience
- The ideal candidate will have strong experience in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, PySpark) and SQL, with the ability to build data-driven solutions and work with large datasets
- Experience with cloud-based AI/ML platforms (Azure, AWS, or GCP) and Power BI for dashboarding and visualization is essential
- The candidate should demonstrate strong organizational and stakeholder management skills, thrive in fast-paced and ambiguous environments, possess strong risk awareness, and have a proven ability to deliver results efficiently

Nice-to-Have Experience

- Experience with Tableau and advanced machine learning model development, deployment, and optimization

Important Notes

- Interview process: 2 rounds - first virtual, second in-person; 30-45 minutes each<

📌 Data Analyst (Toronto)
🏢 Global Technical Talent
📍 Toronto