- Jakarta, Indonesia
Indodana (PT Artha Dana Teknologi) is a OJK-licensed financial technology company that operates a credit marketplace for peer-to-peer loans. Our mission is to achieve financial inclusion by enabling lenders to provide loans to the 100 million underbanked Indonesians.
Leveraging sophisticated big data and artificial intelligence technologies, we connect hundreds of lenders with creditworthy borrowers every day. Our team has combined over 25 years of experience in world class financials, technology and payment companies, such as SoFi, LendingClub, Microsoft, Google, Bank Permata, and DOKU. Together, we are working hard to provide our borrowers with accessible loans and our investors with attractive returns.
- Build credit risk modelling, analytics and reporting for retail customer• Strategically hire, train, and manage risk teams
- Partner with product team to determine how technology help to detect and reduce risk.
- Previous experience building unsecured lending credit risk modelling is highly proffered.
- Analyze key metrics to determine risk.
- Mentoring and supporting junior members of the team will be a key part of the role, in both technical data manipulation skills and documentation delivery.
- Maintain the credit model platform which is utilised by the team and expected to provide advice and guidance on ongoing efficiency gains and new credit modelling methodology.
- Have an undergraduate degree in an analytical discipline (e.g. maths, statistics), however other disciplines will be considered
- Have 3+ experience of working in credit / risk modelling for retail customers especially unsecured lending in bank or non bank
- Have significant experience of credit modelling using statistic tool such as R, Phyton SAS, SQL analytical tools or advanced MS Excel skills
- Have strong verbal and written skills that ensure you can explain technical concepts to less technically focused colleagues and produce suitable documentation
- Be organised, approachable, confident in engaging with stakeholders at all levels and a keen attention to detail
- Experience of reporting in a Financial environment.
- Experience and/or understanding of: data validation and verification techniques, advanced data manipulation techniques, development and production lifecycles, error handling, and automated reporting generation.