Senior Manager, Finance Data Analytics Lead at Questrade Inc

Toronto, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

19 Jun, 26

Salary

155000.0

Posted On

21 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Governance, AI/ML Use Cases, Financial Modeling, Data Infrastructure, Cloud-Native Environments, Data Pipelines, ETL, Python, SQL, Power BI, Tableau, Scrum, Kanban, Data Analysis, Financial Forecasting, Machine Learning

Industry

Financial Services

Description

Questrade Financial Group (QFG), through its companies - Questrade, Inc., Questrade Wealth Management Inc., Community Trust Company, Zolo, and Flexiti Financial Inc., provides securities and foreign currency investment, professionally managed investment portfolios, mortgages, real estate services, financial services and more. Questrade uses cutting-edge technologies to develop innovative products that give customers better, more affordable ways to take control of their money. We are everything a traditional financial institution is not. At QFG, you will be constantly moving forward, bringing the future of fintech into existence. You will be a part of a collaborative team that cares deeply about our mission and each other. Your team members will help you conquer challenges, push boundaries and discover what you are truly capable of. At QFG, we have a culture of innovation where technology serves people—both our team and our customers. We see AI as a collaborative and transformative enabler, and we are seeking forward-thinking individuals who can effectively integrate it into their daily work. The ideal candidate will be a catalyst for change, helping us use AI to create a more efficient and rewarding employee experience while also developing cutting-edge solutions that delight and serve our customers. Join us in shaping a future where AI empowers our team to do their best work and helps us deliver unparalleled customer experiences. This is a place where you can explore, discover and learn with continuous growth. As a diverse and inclusive place to work, with a hybrid working environment you can unleash your creativity and curiosity with no limits. If you share the same sense of infinite possibility, come shape your future at QFG. What’s in it for you as an employee of QFG? Health & wellbeing resources and programs Paid vacation, personal, and sick days for work-life balance Competitive compensation and benefits packages Work-life balance in a hybrid environment with at least 3 days in office Career growth and development opportunities Opportunities to contribute to community causes Work with diverse team members in an inclusive and collaborative environment This job posting is for an existing vacancy. We’re looking for our next Senior Manager, Finance Data Analytics Lead. Could It Be You? The Senior Manager, Finance Data Analytics Lead is a key member of the Finance Business Partner team whose purpose is to deliver insightful financial information and analysis to the business and executive team to support decision-making across the organization while leveraging AI to create efficiencies and streamline work. Working under the direction of the Director, Finance Business Partners, the incumbent supports the finance team broadly as well as the business leaders in product and operations by providing business and financial analysis and management reporting on the bank's unsecured lending business. The Senior Manager, Finance Data Analytics Lead doesn’t just use AI as a buzzword, they use it as a tool to dismantle the friction of legacy finance. By owning the data lifecycle—from infrastructure build to final dataset—you will empower the bank to stop asking "what happened?" and start determining "how do we make it happen?" Need more details? Keep reading… In this role, responsibilities include but are not limited to: Designing and leading the long-term data and AI roadmap for the Finance division, ensuring alignment with the bank’s broader digital transformation goals. Identifying and championing "high-value" AI/ML use cases, such as automated P&L explains, predictive liquidity modeling, and intelligent cost allocation. Defining the standards for data governance, ensuring that every byte flowing through Finance Hub applications is accurate, compliant, and "single-source-of-truth" certified. Acting as a "bilingual" leader who can explain complex technical architectures to the CFO and financial concepts to the Engineering team. Leading the development of machine learning models to improve the accuracy of Net Interest Margin (NIM) and Return on Equity (ROE) projections. Implementing AI-driven monitoring to detect "fat-finger" manual entry errors or suspicious patterns in the General Ledger (GL) in real-time. Building automated frameworks for "What-If" analysis, allowing leadership to simulate the impact of interest rate hikes or economic downturns instantly. Overseeing the migration of legacy "siloed" finance data into cloud-native environments (e.g., Snowflake, Databricks, or Azure). Leading the end-to-end building of core data infrastructure. Designing and implementing the pipelines and environments necessary to support advanced financial modeling. Architecting and maintaining specialized datasets within Finance Hub applications. Translating complex business logic into structured data assets that enable seamless reporting and self-service analytics for the entire department. Driving the transition from legacy, manual workflows to automated, real-time analytics. Overseeing the migration of descriptive reporting into predictive and prescriptive models, utilizing AI to eliminate the "heavy lifting" of data reconciliation. Managing a team of data analysts, fostering a culture of technical excellence. Ensuring that your team balances regulatory rigor with the agility needed to provide "what-if" forecasting and strategic insights. Establishing a unified data layer that integrates disparate sources—including Treasury, Risk, and Retail Banking—to ensure consistency in reporting. Replacing manual Excel-based reconciliation with Python-based ETL (Extract, Transform, Load) pipelines to reduce "human-in-the-loop" risks. Building and managing a high-performing team of Data Analysts. Monitoring and reporting on department success using metrics such as Automation Rate, Model Accuracy, and Reduction in Reporting Cycle Time. So are YOU our next Senior Manager, Finance Data Analytics Lead? You are if you… Hold a post-secondary degree or equivalent in Computer Science or a related field Have 5+ years of related work experience in Data Analytics or Data Transformation, with at least 2 years at a leadership level Have mastery of regression, time-series analysis, and machine learning specifically applied to financial forecasting Have a deep understanding of how to design scalable data pipelines and "Data Lakes" within a banking environment (e.g., Snowflake, Databricks) Have strong SQL proficiency for data extraction and Python or R for building automated analytical engines Are able to transform large data sets into intuitive executive dashboards using Power BI or Tableau Understand the data nuances of various banking products—ranging from simple savings accounts to complex derivatives and structured finance Possess competency in analyzing interest rate risk, liquidity ratios, and funds transfer pricing (FTP) Are able to ensure AI models are not "black boxes," providing the transparency required by internal audit and external regulators Possess the "soft power" required to convince traditional finance teams to abandon manual processes in favor of automated AI tools Are able to evaluate the ROI of various analytics projects and focus the team on the highest-impact initiatives Have experience leading data teams using Scrum or Kanban to ensure iterative delivery and constant alignment with business needs Have a proven track record of recruiting and upskilling "hybrid" talent who understand both code and capital Have strong communication skills to collaborate effectively with multiple levels of leadership, both verbally and in writing Are pro-active and results-driven Are able to multitask and work well under pressure, maintain strong attention to detail and prioritize work within tight deadlines Have advanced proficiency in Excel Have experience in banking, with emphasis on Data Analytics, Business Analytics, Data Modelling, Data Architecture, Machine Learning, Prompt Engineering, and AI integration and implementation Additional kudos if you… Have NetSuite and Oracle EPBCS experience Compensation Information: Base salary range: $135,000 - $155,000 The final compensation package will be commensurate with the successful candidate's experience, skills, and geographic location (Canada). It includes a comprehensive benefits plan and a competitive incentive (bonus) program for Full-Time Permanent roles. Sounds like you? Click below to apply! #LI-NP1 #LI-Hybrid At Questrade Financial Group of Companies, with multiple office locations around the world, we are committed to fostering a diverse, inclusive and accessible work environment. This is an environment where individuals are treated with dignity and respect. Here, the unique skills and experience you bring will be valued. You will be supported and motivated, so that you can harness your unlimited potential. Our team reflects the diversity of the communities we serve and operate in. Having a collaborative and diverse team helps us push boundaries to bring the future of fintech into existence—not only for the benefit of our customers, but for those who build their career with us. Questrade Financial Group of companies Applicant Tracking System utilizes artificial intelligence (AI) for application screening. The AI system operates on predetermined criteria, with final decisions subject to human review. Candidates selected for an interview will be contacted directly. If you require accommodation during the recruitment/selection process, please let us know and we will work with you to meet your needs.

Responsibilities

The role involves delivering insightful financial analysis to support decision-making across the organization while leveraging AI to create efficiencies and streamline work, specifically supporting the unsecured lending business analysis and management reporting. Key duties include designing the long-term data and AI roadmap for Finance, championing high-value AI/ML use cases, and overseeing the migration of legacy finance data to cloud-native environments.