Jobs at Boku (Now Hiring) — 4 open

 

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

• 8+ years of relevant experience in data analytics, business intelligence, analytics engineering, or a related field
• University degree or equivalent practical experience preferred