Data Analyst, Product

About the Company

Kraken, established in 2011 and operated by parent company Payward, is a leading global cryptocurrency platform serving over 10 million customers worldwide. It offers a broad suite of financial services including spot trading, margin trading, futures, staking, and OTC, catering to both individual investors and large institutions. Payward has built a modern financial infrastructure platform designed to support an open and accessible global financial system.

Team and Role Overview

The Data Analyst, Product, will be a vital part of the Pro product team, working remotely to convert intricate data sets into clear, actionable insights that enhance user experience, drive feature innovation, increase engagement, and inform high-level product decisions. The role entails complete ownership of data operations from building production-grade data pipelines and dbt models to developing dashboards and metric frameworks. This position includes establishing key performance indicators from scratch, managing experimentation workflows with A/B testing and causal inference, and interpreting findings into strategic product guidance.

The successful candidate will also actively integrate AI tools into their workflows, leveraging large language models and generative AI to improve analytics processes. Collaborative interaction across cross-functional teams is essential, with an emphasis on combining deep domain knowledge about user behaviors and retention funnels with rigorous data quality standards.

Key Responsibilities

• Act as a full-stack data analyst within the Pro team, fully owning your assigned domain while collaborating with colleagues across the team.
• Design, develop, and evolve dashboards, key metrics, and analytical frameworks to influence business decisions at senior levels.
• Construct and maintain scalable data infrastructure, including dbt models and production data pipelines to support comprehensive reporting.
• Lead product experimentation initiatives by crafting and managing A/B test frameworks, applying causal inference techniques, and synthesizing outcomes into decisive strategic recommendations.
• Drive technical standards and direction within the data team, prioritizing data quality and engineering best practices.
• Incorporate AI technologies into data workflows to create tangible business value, such as LLM-augmented pipelines and AI-assisted analytics.
• Communicate insights effectively through clear, data-driven storytelling adapted to technical and non-technical audiences, including leadership.

Required Qualifications and Skills

• Over 7 years of experience in data analytics or analytics engineering within fintech, payments, financial markets, or cryptocurrency sectors where data accuracy and scalability are paramount.
• Direct expertise with advanced trading products in equities, cryptocurrency, or other asset classes, complemented by professional experience either in financial markets, on a trading desk, or as a professional trader.
• Proven skills designing and managing production data pipelines, with hands-on familiarity using dbt and Airflow or similar orchestration systems.
• Expert-level proficiency in SQL, including complex queries with joins, CTEs, and window functions, alongside strong Python programming capabilities for pipeline development and data analysis.
• Experience designing and executing A/B testing and experimentation frameworks, applying causal inference methods, and providing actionable growth recommendations based on test results.
• A track record of leading cross-functional data projects from conceptualization to implementation, demonstrating clear business impact.
• Excellent communication skills with the ability to simplify complex data concepts for diverse audiences.
• A degree in software engineering, economics, or a quantitative discipline focusing on analytical rigor.
• Residency in Canada, the US, the UK, or the EU and fluency in English.

Preferred Additional Experience

• Familiarity with deploying analytics pipelines enhanced by large language models or AI-assisted workflows in production environments.

Additional Information

Applications are accepted continuously unless a specific deadline is declared. Candidates may redact personal information related to age or education dates on their resumes. The company evaluates candidates with criminal histories in compliance with the San Francisco Fair Chance Ordinance. Kraken is committed to diversity and equal opportunity, fostering an inclusive culture free from discrimination based on characteristics protected by law.

Assessment tests relevant to the role may be part of the hiring process, focusing on job-related skills and competencies. These assessments are balanced with experience and interview outcomes.