Data Analyst, Product

Responsibilities

• Operate as a full-stack data analyst within the Pro team, owning your domain completely while collaborating closely with colleagues across the pod.
• Own the design and evolution of dashboards, north star metrics and analytical frameworks that drive decisions at the highest level of the business.
• Build and maintain data infrastructure at scale, from scalable dbt models and production pipelines to full-funnel reporting that powers cross-functional teams.
• Lead experimentation across the Product domain by designing and owning A/B testing frameworks, applying causal inference techniques and turning results into clear, confident recommendations that influence product strategy.
• Influence technical direction across the data team, contributing to how we build, what we prioritise and how we raise the bar on data quality and engineering standards.
• Embed AI tooling into your workflow in ways that have tangible business impact, including LLM-augmented pipelines and GenAI-assisted analytics workflows.
• Deliver insights through clear, data-driven storytelling to technical and non-technical audiences, including senior leadership.

Requirements

• 7+ years of experience in data analytics or analytics engineering, ideally within fintech, payments, financial market or crypto where data quality and scale are non-negotiable.
• Hands-on experience with advanced trading products and solutions in equities, crypto, or other assets. Professional background working within financial markets or on a trading desk, or professional trader.
• Hands-on experience building and owning production data pipelines, with strong familiarity with dbt and Airflow or equivalent orchestration tools.
• Full mastery of SQL including complex joins, CTEs and analytical functions, alongside strong Python proficiency for pipeline development and analysis.
• Hands-on experience designing and running A/B tests and experimentation frameworks, with the ability to apply causal inference techniques and translate results into clear growth recommendations.
• Demonstrated experience leading cross-functional data initiatives from design to delivery, with measurable business outcomes.
• Strong communicator who can simplify complex data ideas for both technical and non-technical audiences.
• A degree in a field emphasising analytical rigour such as software engineering, economics or a hard science.
• Based in Canada, the US, the UK or the EU and fluent in English.

Nice-to-Haves

• Experience with LLM-augmented analytics pipelines or AI-assisted workflows in a production environment.