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описание
Based in Canada, the US, the UK, or the EU, and candidates may be asked to complete job-related skills or work-style assessments.
Payward is the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services, and CF Benchmarks, and has spent the last 15 years building a modern financial infrastructure platform to advance an open, global financial system. Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions worldwide, offering spot trading, margin, futures, staking, and OTC services.
задачи
Operate as a full-stack data analyst within the Pro team, owning the 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 they build, what they prioritize, and how they raise the bar on data quality and engineering standards;
Embed AI tooling into the 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.
требования
7+ Years of experience in data analytics or analytics engineering, ideally within fintech, payments, financial market, or crypto;
Hands-on experience with advanced trading products and solutions in equities, crypto, or other assets, or a professional background working within financial markets or on a trading desk, or as a 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;
Degree in a field emphasizing analytical rigor such as software engineering, economics, or a hard science;
Fluent in English;
Nice to have: Experience with LLM-augmented analytics pipelines or AI-assisted workflows in a production environment.
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