Data Analyst

LanceSoft; Toronto; Hybrid; CAD 70,000 - 90,000; Full time

Job summary

A leading staffing agency in Toronto is seeking an experienced Data Analyst to join a diverse team supporting the Capital Analytics Project. The ideal candidate will have at least 2 years of experience, including database design, SQL, and Python, fostering personal development through ongoing coaching. This role offers a hybrid work schedule and an opportunity to learn about global capital markets within a high-performing environment.

Benefits

In-depth training

Ongoing coaching and feedback

Opportunities for personal development

Qualifications

• 2 years of experience as Data Analyst.
• Recent experience with database design is critical.
• 2+ years of experience with SQL.
• 2+ years of experience with Python.

Responsibilities

• Assist in the processing and validation of large volumes of financial data.
• Collaborate to troubleshoot data discrepancies.
• Perform reconciliations for accuracy.
• Participate in process improvements related to data management.
• Generate reports and provide analysis.
• Help leverage data for opportunity identification.

Skills

Data analysis

SQL

Python

Database design

Education

Post-secondary education in Computer Science

Tools

Excel

Power BI

Job description

Overview

Location Address: 40 Temperance Street 7th Floor (40T-7)
Hybrid: 4 days (Anchor days: Tuesday, Thursdays. Days will change based on the project need)
Contract Duration: 02/23/2026 to 02/22/2027
Possibility of extension: Yes, extension based on performance
Conversion to FTE: May be, based on performance and business needs
Schedule Hours: 9am-5pm Monday-Friday; standard 37.5 hrs/week

Story Behind the Need

Business group: Global Banking and Markets (GBM)

Project: Capital Analytics Project

Global Banking and Markets (GBM) provides corporate and institutional clients with lending and transaction services, investment banking, advice, and access to capital markets. GBM is a full-service wholesale bank in the Americas, with operations in several countries, serving clients across Canada, the United States, Latin America, Europe, and Asia-Pacific.

Reason: To support Client Insight & Analytics' day-to-day activities, to support Capital Analytics project.

Candidate Value Proposition

• You’ll be part of a diverse, collaborative, innovative, and high-performing team.
• In-depth training to prepare you for the role, as well as ongoing coaching and feedback to help you succeed!
• You will be provided with an excellent opportunity for learning and personal development, especially if you wish to gain exposure to global capital markets, and the critical real-time financial data needed and utilized to move key business lines forward.

Key Accountabilities

• Assist in the processing and validation of large volumes of financial data from various sources.
• Collaborate with cross-functional teams to troubleshoot data discrepancies and resolve inquiries promptly.
• Perform reconciliations between internal systems to ensure accuracy and integrity.
• Participate in the development and implementation of process improvements related to data management and reconciliation procedures.
• Generate reports and provide analysis to support decision-making processes.
• Help leverage internal and external data to facilitate opportunity identification.

Must have Skills/Experience/Competencies

• 2 years of experience as Data Analyst
• Recent experience with database design is critical for the role
• 2+ years of experience with SQL
• 2+ years of experience with Python

Nice to have

• Advanced experience with Excel, Power BI
• Knowledge of the capital markets and wholesale banking business.

Education

• Post-secondary education in Computer Science, or a related field.

Best vs. Average Candidate

The ideal candidate will be an experienced Data Analyst with strong experience with database design, SQL and Python. Recent experience with capital markets and wholesale banking business is very nice to have. Someone who is curious to learn and grow within the team structure is highly preferred.