Intermediate Data Scientist

Number of Positions: 2

Start Date: November 23, 2026

Duration: 12 months, with potential for extension or conversion

Location: Toronto, ON

Work Arrangement: Hybrid – 4 days onsite per week

Schedule: Monday to Friday, 9:00 AM – 5:00 PM

About the Role

We are seeking two Data Analyst III professionals to join an Analytics and AI team supporting a new AI-focused initiative within a leading financial institution.

This role is approximately 60% Data Science and 40% Data Analytics/Business Intelligence, with a strong emphasis on Python-based data analysis, large-scale data processing, and analytical model development.

The ideal candidate will have strong hands-on experience with Python, particularly PySpark, Pandas, and NumPy, along with SQL, Databricks, Azure, and Power BI. They will be responsible for working with large datasets, developing analytical solutions, supporting machine learning initiatives, and translating findings into meaningful business reporting.

Key Responsibilities

• Analyze, manipulate, and process large datasets using Python, particularly PySpark, Pandas, and NumPy.
• Develop and maintain data pipelines, transformation processes, and analytical datasets using Databricks.
• Apply statistical analysis and machine learning techniques to identify trends, patterns, and business opportunities.
• Build and support analytical models and data-driven solutions for AI initiatives.
• Write complex SQL queries for data extraction, transformation, and analysis.
• Develop interactive Power BI dashboards, reports, and visualizations.
• Collaborate with business partners and technical stakeholders to translate requirements into analytical solutions.
• Support data quality, model deployment, monitoring, and ongoing optimization.

Required Qualifications

• 3–7 years of relevant experience in Data Science, Data Analytics, or Advanced Analytics. Candidates with 3+ years of strong hands-on experience will be considered.
• Strong Python programming skills with hands-on experience using:
• PySpark for large-scale data processing and transformation.
• Pandas for data manipulation, cleaning, and analysis.
• NumPy for numerical computing and statistical analysis.
• Scikit-learn, TensorFlow, and/or PyTorch for analytical and machine learning applications.
• Strong SQL skills, including complex queries and data extraction.
• Hands-on experience with Databricks and large datasets.
• Experience with Azure cloud-based data and AI/ML environments.
• Strong Power BI skills, including dashboard development, reporting, and visualization.
• Experience with analytical model development and machine learning techniques.
• Strong analytical, communication, and stakeholder management skills.

Nice to Have

• Experience with Tableau or other data visualization platforms.
• Exposure to AWS or Google Cloud Platform.
• Experience with feature engineering, model training, deployment, and optimization.
• Knowledge of supervised and unsupervised machine learning techniques.
• Undergraduate or advanced technical degree in Computer Science, Mathematics, Statistics, Engineering, Finance, or a related field.

Ideal Candidate

A Junior-to-Intermediate Data Scientist or technically strong Data Analyst with hands-on Python experience, particularly PySpark, Pandas, and NumPy, and the ability to work with large datasets. Candidates should also bring Databricks, SQL, Azure, and Power BI experience, with an interest and background in AI, machine learning, and analytical model development.

**As part of our recruitment process, artificial intelligence (AI) tools may be used to assist with certain hiring activities, such as reviewing applications and assessing candidate qualifications. All hiring decisions involve human oversight and are made by individuals involved in the recruitment process.**