Data Analyst, Product (Banking and Payments)

ABOUT FLOAT Float is on a mission to simplify finance for Canadian businesses, empowering them to eliminate complexity and unlock new opportunities. Through our innovative platform, Float enables businesses to streamline financial operations and optimize cash flow, so they can focus on what matters most: growth.  As one of Canada’s fastest growing companies https://www.theglobeandmail.com/business/rob-magazine/top-growing-companies/article-ranking-canadas-top-growing-companies-of-2024/ and top-rated startups in 2025 https://www.linkedin.com/posts/floatfinancial_were-proud-to-share-that-float-has-been-activity-7387093684720300032-2DDz/, 2024 https://www.linkedin.com/pulse/linkedin-top-startups-2024-15-canadian-companies-rise-linkedin-news-llihe/ and 2023 https://lnkd.in/TSU23CA, Float is customer-obsessed, passionate and entrepreneurial, with a team that includes leaders from Uber, Stripe, Shopify, Top Hat, Ada, Doordash, Snowflake, and Wealthsimple. At Float, everyone is an owner, bringing their unique perspective to our team and product. Your voice is important, and we take having a culture based on feedback seriously. We openly share our thoughts and differing opinions so we can continue to improve. We do our best to keep our decision-making decentralized so that all team members feel ownership in our success. OUR PRODUCT Float is Canada’s intelligent financial operating system, combining modern financial services and software to help businesses spend, save, and grow. Trusted by more than 7,500 Canadian companies, Float provides high-limit corporate cards, automated expense management, next-day bill payments, high-yield accounts, and industry-leading support, all built in Canada, for Canada. Float recently announced our $85 million Series C https://floatfinancial.com/press/float-financial-raises-cad-85-million-series-c, and is backed by world-class investors, including Inovia Capital, Growth Equity at Goldman Sachs Alternatives, OMERS Ventures, and Silicon Valley Bank. Our team is a collection of ambitious, collaborative and mission-driven people from all walks of life but with one goal: helping Canadian companies not just survive but thrive. And we’re looking for bold innovators to help shape the future of business finance in Canada. AI USE IN OUR HIRING PROCESS We use technology, including artificial intelligence (AI), to support parts of our hiring process. This may include AI-assisted scheduling and candidate communications, and AI-generated interview notes, guides or summaries to help our team focus on the conversation. All hiring decisions are made by our hiring team. ABOUT THE ROLE Float is building the financial operating system for Canadian businesses — corporate cards, business bank accounts, bill payments, all in one place. Reporting to the Head of Data, this role is embedded inside the product teams behind two of those core pillars: banking infrastructure and payments. Both are high-complexity, high-stakes areas that generate a dense mix of financial, behavioral, and operational data. This role owns that data layer. You're building cohorts before anyone asks, designing measurement frameworks before features go to engineering, and debugging numbers to the source — pipeline issue, definition mismatch, or real product signal. You're also someone who uses AI to move faster without losing rigour. Getting useful outputs from a model means knowing the business and data well enough to give it the right context — that's part of the job too. WHAT YOU'LL BE DOING - Define what needs to be measured before features ship and support the instrumentation to measure it. You translate roadmap decisions into measurement requirements. - Design and get broad alignment on measurement frameworks before features go to engineering — hypothesis, cohorts, success criteria. - Design and analyze experiments - structure A/B tests for product changes. Define the hypothesis, select the right unit of randomization, size the experiment for sufficient power and interpret results with statistical rigour - Own the metrics and dashboards for Banking and Payments. Every number is traceable to a reliable dbt model. You keep them accurate. - Own data quality in your product area — audit dbt models, write clear briefs for analytics engineering, flag gaps before they become problems. - Run cohort and retention analysis natively — activation sequences, behavioral funnels, leading vs. lagging indicators. Diagnose which lever moves the number, not just what happened. - Debug ambiguous numbers to the source — pipeline issue, definition mismatch, or real product signal. You close the loop. - Write expert SQL and bring statistical rigour — cohort construction, retention calculations, confidence intervals, significance testing. You know when you have enough signal to act. - Use AI as a multiplier — accelerate analysis, generate first-pass SQL, and pressure-test hypotheses faster than you could alone. You know how to give a model the business and data context that makes its outputs impactful. - Take your share of ad-hoc requests on rotation — owning your product area gives the broader data team meaningful breathing room. WHAT SUCCESS LOOKS LIKE - Get Embedded: Both team leads treat you as the owner of their data layer. KPI definitions are agreed upon, documented, and tied to reliable dbt models. Gaps are flagged with a fix in motion. - Build the Measurement Layer: Features ship with measurement frameworks designed upfront. Dashboards for the core banking and payments metrics are clean, trusted, and traceable. - Drive Product Evidence: Product decisions are shaped by your analysis before they are made. When a team lead is asked by leadership whether a feature is landing, they already know — because you’ve built the infrastructure that makes the question answerable. WHAT WE'RE LOOKING FOR - Product analytics depth — you've been embedded in a product team, own activation funnels and cohort retention natively, and know how to instrument a feature before it ships. - Experimentation and measurement design — you design A/B tests and quasi-experiments from the ground up: hypothesis, randomization unit, sample size and power calculations, guardrail metrics, and holdout design. You build pre/post and diff-in-diff analyses where randomization isn't feasible, and you know how to communicate the difference in confidence between the two - Data layer ownership — you're the DRI for data quality in your product area: auditing dbt models, writing briefs for analytics engineering, and debugging ambiguous numbers to the source. - Expert-level SQL — you build complex multi-step queries across large behavioral datasets, optimize for performance, and explain the logic to non-technical stakeholders. - Statistical reasoning — you understand distributions, confidence intervals, significance testing, and sample size constraints. You design for confounders, know when you have enough signal, and communicate uncertainty in plain language. - Data modeling literacy — you translate business logic into data requirements, specify the grain a table needs, and have informed opinions on how metrics get structured in dbt. - Comfort with imperfect data — you make a reasoned call, state your confidence level, and give stakeholders something actionable rather than waiting for clean infrastructure. - Stakeholder fluency — you work effectively across Product, Design, Engineering, and Product Marketing, and hold your ground respectfully when data contradicts what the team wants to believe. - AI as an accelerator — you've used LLMs to write SQL, draft frameworks, or structure analysis, and you know where they're reliable and where they need guardrails. - 2–4+ years in product analytics, ideally embedded in a product team at a high-growth fintech or SaaS company. - BI tool experience — Metabase, Looker, Tableau, Sigma, or similar. - dbt-comfortable (reading models, understanding lineage) with Snowflake or a comparable cloud warehouse. - Fintech familiarity — attach rate, payment rails, KYC, AP workflows, pre-authorized payments, balance/deposit metrics, churn dynamics — is a meaningful differentiator. OUR HIRING PHILOSOPHY We hire for character, curiosity, and learning velocity before credentials. Titles matter less than impact, and every hire is expected to raise the bar for Float as a whole. WHY YOU SHOULD JOIN - Work at one of Canada's fastest-growing fintech companies - Make a real impact in a high-autonomy, high-growth role - Collaborate with an ambitious and supportive team - Competitive compensation, equity options, and benefits - Hybrid work model – we are based in Toronto with in-office days for connection and collaboration - Enjoy catered team lunches every Tuesday, Wednesday and Thursday - Bring your pup to our dog-friendly office - Thrive in a high-trust, high-performance culture where your work truly matters IN SHORT At Float, you’ll thrive if you’re bold, curious, and eager to make a real impact. We're building something special—and having a lot of fun along the way. If you’re excited to build, grow, and win together, we’d love to meet you. We’re committed to building a workplace that’s welcoming and accessible for everyone. If you need any accommodations during the hiring process or once you join Float, just let us know! You can reach out to Vic https://www.linkedin.com/in/victoria-boult-b21b2053/ (victoria@floatfinancial.com), and we’ll work with you to make sure you have what you need to succeed.