Jobs in Canada

Analyste Financier in Toronto

32 active opportunities · Updated October 2026

Explore current analyste financier jobs in Toronto. Filter by work mode, employment type, experience, department, date posted and distance.

O
📍 Toronto, Ontario, Canada· Full-time
✓ High-confidence listingCompany trend -63.6%

From C$124K/yr

Quick readStrong listing-quality and freshness signals

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. THE OPPORTUNITY Auth0 is a leading identity platform that secures billions of logins every year for organizations around the world. We're trusted by enterprises, startups, and developers to simplify identity and access management across any application, on any platform, anywhere. We're seeking a Product Operations Manager with a strong focus on data and analytics to help us turn raw data into meaningful business insights. Reporting to the Head of Product Operations, you'll be the person who looks at what the data is telling us and connects it to what it means for the business — revenue, retention, growth, and product direction. This is not a pure analyst role. You'll need to understand the business deeply enough to ask the right questions of the data, and communicate the answers in a way that drives real decisions. You're equally comfortable working in a dashboard as you are in a leadership meeting explaining what the numbers mean and why they matter. KEY RESPONSIBILITIES: Turning Data Into Business Insight: Take raw product and business data and translate it into clear narratives about what is working, what isn't, and where the opportunity lies. Build and maintain decks and dashboards that go beyond reporting numbers, telling a story and driving action. Work with Product to define the KPIs and metrics that matter most to the business and ensure teams understand how to track them, and how their work connects to those outcomes. Ident

SQLAWSRestMachine Learning
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$172K/yr

Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data Science & Analytics is at the heart of Lyft's products and decision-making. The Rider Experience team sits at the center of how millions of riders discover, choose, and return to Lyft. We are hiring a Data Science Manager to lead our Toronto-based science & analytics team that turns rider behavior into product strategy. This role owns the analytical foundation behind our most consequential rider-facing decisions: how we measure experience quality, where friction costs us retention, and which bets move rider LTV. You will set the measurement and experimentation standards for rider product squads, and translate ambiguous business questions into rigorous, decision-ready analysis that shapes roadmap and investment. You will also lead the team's transition to AI-native data science and analytics workflows, embedding AI tooling into how we explore data, make decisions, and ship products. Responsibilities: Lead and grow a high-performing team of data scientists and analysts with diverse backgrounds Define and drive the data science vision, strategy, and roadmap, aligning with business and product objectives to improve market competitiveness and rider experience Provide strong technical guidance and coaching to the team on complex data science problems Champion data-driven decision-making and prioritization by partnering with product managers, engineers, marketers, and leaders to translate insights into decisions and action Lead deep-dive analyses into large-scale datasets to identify opportunities for improving rider app experience and overall rider product health Ensure robust experimentation and causal inference methodologies are applied to measure the impact of new features and strategies Mentor and guide the professional and technical development of your team members; help develop the

Machine LearningAIGo
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