Senior Data Scientist - Fraud Modelling

Company Description

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.

Job Description

• Identify new, emerging fraud and abuse trends/patterns through data analysis and metrics tracking to mitigate risks
• Recommend short-term solutions and long-term prevention strategies at the strategic and tactical levels, balancing the business vision and implementation feasibility
• Assess, define, and optimize relevant operational fraud metrics for long-term tracking
• Collaborate with internal stakeholders (Risk, Data Science, Engineering, Product Management, Operations, and others) to ensure proper enforcement of fraud prevention rules and detection strategies
• Engage with external partners and stakeholders, when necessary, to drive operational improvements to manage and mitigate fraud risks
• Identify blockers, conflicts, and risks to fraud projects and seek solutions to drive timely execution

Qualifications

• Undergraduate degree, in quantitative majors preferred (e.g. finance, economics, engineering, mathematics, statistics) but not required
• At least 2 years of experience within the Risk or Analytics domain or Data Scientist, within banking/finance/payment will be a plus.
• Analytically sound: structured, facts-oriented, data-driven. Able to derive clear, actionable insights from a large amount of data.
• Strong in SOP building, governance principles (maker/checker), highly informed with operational metrics (SLA, exceptions, escalations)
• Strong proficiency in Google Suite and other data skills (SQL/Big Query, Excel, Python preferred)
• Excellent written & verbal communication skills to effectively collaborate and exchange information across stakeholders of various backgrounds and technical levels