Risk Data Analyst at Tiko ( Formally Triggerise)

The Job

The Risk Analyst uses data analysis, visualization, and modelling techniques to provide insights, identify trends, and detect fraud risks—offering actionable recommendations that strengthen decision-making and operational efficiency across the organization.

You'll also be responsible for:

• Creating and maintaining risk-related dashboards for local operations based on programme, donor, and operational needs.
• Managing and organising data from multiple sources, including those not captured within internal systems.
• Developing and maintaining reports that triangulate data to support the Risk Management function with information about actors on our platform.
• Analysing data to detect risk and fraud patterns and reporting these insights to the Risk Management team.
• Building tools that help local and global teams identify trends, understand risks, and make informed decisions to improve process controls.
• Supporting donor reporting where needed.
• Participating actively in meetings and projects, collaborating closely with team members, and staying up to date with the latest data and fraud detection practices.
• Supporting colleagues and contributing to other projects across the organisation as required.

About You

• You are a tech-savvy analytical thinker who enjoys solving problems, uncovering insights, and designing tools that help teams make informed decisions. You work well with people, stay calm in moments of frustration, and bring a strong sense of ownership and attention to detail to your work.

Requirements

• Proven hands-on experience managing end-to-end analytics projects.
• Ability to build dynamic analytical models using advanced formulas in Excel and Google Sheets.
• Strong SQL skills, including writing complex queries using joins and window functions to validate large datasets.
• Experience developing interactive dashboards, using table calculations, storytelling features, and advanced filtering.
• Ability to implement best-practice visualisation design principles and publish dashboards to Tableau Server/Cloud.
• Proficiency in Python or R for advanced analytics and visualisation (e.g., scikit-learn, matplotlib, Plotly).