Business & AI Process Automation Analyst

About the role

We are looking for a Business & AI Process Automation Analyst to help our Corporate Development team turn business data and operational processes into better decisions, faster execution, and measurable improvements.

This is a hybrid business-and-technology role for someone with a Computer Science, Information Systems, or related background who enjoys working closely with business users. You will work across Corporate Development, Product, Operations, Finance, Engineering, Legal, Compliance, and other stakeholders. 

Cross-functional and external stakeholder delivery

Manage operational requirements, timelines, and issue resolution across Corporate Development, Product, Operations, Finance, Engineering, Legal, Compliance, and other internal teams.

Manage end-to-end operational workflows for new digital asset integrations and asset offerings across products — from initial assessment through to live launch and ongoing maintenance.

Oversee and execute platform updates for critical asset events: token migrations, smart contract swaps, protocol upgrades, rebrands, and asset deprecation/offboarding. 

Act as the primary operational point of contact for external project teams, foundations, and key stakeholders.

Coordinate internally to facilitate joint promotional campaigns, user engagement activities, and ecosystem growth initiatives with external partners.

AI-enabled process automation

Identify repetitive analytical and operational work that can be improved with AI, LLMs, Python, SQL, APIs, low-code tools, or workflow platforms.

Design and implement multi-step workflows with prompts, data transformations, validation rules, operating procedures, and clear business ownership.

Test and monitor workflows for accuracy, edge cases, failures, exceptions, human review, approval gates, escalation, and safe fallback procedures.

Business analysis and decision support

Translate ambiguous business questions into structured analysis, measurable metrics, data requirements, and actionable recommendations.

Analyse business performance, product and operational trends, opportunities, bottlenecks, and process effectiveness.

Build dashboards, reports, and executive-ready presentations, clearly explaining assumptions, trade-offs, limitations, and impact.

Data quality and control

Investigate discrepancies across reports, systems, data sources, and metric definitions, and establish consistent business logic.

Document data sources, transformations, analytical assumptions, ownership, and control requirements.

Identify and escalate data-quality, access-control, privacy, security, and operational risks, ensuring AI-assisted outputs are validated before use.

3+ years of relevant professional experience in business intelligence, business analytics, process automation, operations analytics, or a related role.

A degree in Business Administration or Computer Science, Data Analytics, Information Systems or a related discipline; equivalent practical experience is also welcome.

Practical experience using AI-enabled tools, LLMs, workflow automation, low-code platforms, or agentic workflows to improve analytical or operational processes.

Strong business judgment and the ability to connect analysis to priorities, trade-offs, and measurable outcomes.

Strong written and verbal communication skills, with the ability to work effectively across technical and business teams.

A structured, detail-oriented approach to problem-solving and the ability to prioritise effectively when requirements are ambiguous or changing.

Based in Hong Kong and able to work with stakeholders across different functions and time zones.

Experience building dashboards, reports, data pipelines, or analytical tools using Power BI, Tableau, Looker, Excel, or equivalent tools.

Experience with Python and SQL for data preparation, analysis, automation, or workflow development.

Experience building or implementing AI agents or multi-step workflows with exception handling and human handoffs.

Experience with APIs, Git, n8n, Databricks, cloud data tools, or workflow-orchestration platforms.

Exposure to financial services, fintech, digital assets, payments, trading, capital markets, or another fast-moving technology environment.