Boku Inc. (BOKU.L) is the leading global provider of local mobile-first payments solutions. Global brands including Amazon, DAZN, Meta, Google, Microsoft, Netflix, Sony, Spotify, and Tencent rely on Boku to reach millions of new paying consumers who do not use credit cards with our purpose-built payment network of more than 300 local payment methods across 70+ countries. Every year, Boku processes over $10 billion in value for our customers. Incorporated in 2008, Boku is headquartered in London and San Francisco and has employees in over 39 countries around the world, including Brazil, China, Estonia, Germany, Ireland, Japan, Singapore, and the UAE. Boku is a truly global company that takes pride in its diversity and thriving equal opportunity workplace.
Role Purpose
As a Senior Business Data Analyst within Boku’s Data, AI & Analytics Team, you will support strategic partners across the APAC region through operational and data-driven analysis, investigations, troubleshooting and reporting.
This role combines technical analysis, commercial collaboration, and direct partner interaction. Technical teammates are globally distributed across time zones, while day-to-day commercial and partner interaction will happen primarily within the Singapore time zone and offices in Singapore.
A large part of this role involves dealing with ambiguity. Often, there will be no pre-existing answer to the questions being asked, requiring independent investigation using internal data and collaboration with technical and commercial stakeholders.
Key Responsibilities
Partner Analytics & Investigation
- Investigate partner concerns relating to conversion performance, churn, segmentation,behavioural trends, and payment funnel optimization
- Analyse large-scale operational datasets to identify trends, anomalies, and opportunities for improvement
- Perform structured investigations into ambiguous operational and commercial questions, often establishing new analytical frameworks and iterating on evolving methodologies
- Support troubleshooting and root-cause analysis across payment flows, user funnels, and operational workflows
Reporting & Analytics
- Build reporting, dashboards, and analytical models using SQL, dbt, Tableau, and related tooling
- Work with large-scale operational and financial datasets across markets, payment methods, and products
- Contribute to the evolution of analytical workflows, automation, and AI-assisted tooling, helping build everything from pipelines to dashboards and reports
- Leverage cutting-edge AI tools—including chat-based AI assistants, AI coding assistants, and AI agents—to improve analytical workflows, automate repetitive tasks, accelerate problem-solving, and evaluate emerging AI technologies to solve complex business challenges.
- Demonstrate curiosity and a self-learning mindset by continuously exploring and adopting new AI capabilities to enhance productivity, innovation, and business outcomes.
Stakeholder & Commercial Collaboration
- Participate in operational meetings, troubleshooting discussions, presentations, and business review sessions with internal commercial teams and external strategic partners
- Follow up on issues raised during meetings, taking ownership and helping drive issues toward resolution
- Help bridge the gap between technical and non-technical stakeholders, translating complex technical and analytical concepts into clear, actionable communication
- Build strong working relationships and trust with commercial teams and external partners through thoughtful, reliable, high-quality analytical work
Key Skills and Competencies
- Comfortable operating with a high degree of ambiguity and autonomy
- Naturally curious and commercially minded
- Strong problem-solving and analytical reasoning skills
- Experience using BI tooling, SQL, and modern cloud data warehouses such as Redshift, Snowflake, or BigQuery
- Understanding of analytics engineering concepts and modern data transformation workflows
- Stakeholder management expertise, with the ability to clearly communicate findings to both technical and non-technical audiences, translating analysis into actionable recommendations
- Takes ownership of outcomes, builds stakeholder trust, and consistently delivers high-quality work
- Proven ability to work directly with strategic enterprise partners who have high expectations for analytical quality, responsiveness, and communication
- An autodidact who is continuously learning new concepts, tools, and modern approaches to analytics and automation, including the use of AI agents
Preferred
- Familiarity with dbt, Tableau, Python, or related analytics tooling
- Background in payments, fintech, subscriptions, e-commerce, or digital platforms
- Experience with customer-facing work involving commercial teams and external stakeholders
- Exposure to AI-assisted development, data analysis, or automation tools, alongside a demonstrated curiosity for applying emerging AI technologies to real-world problems
Qualifications
- 5+ years of relevant experience in data analytics, business intelligence, analytics engineering, or a related field
- University degree or equivalent practical experience preferred
