Branch-based microfinance and digital payments for women-led MSMEs in Indonesia
Amartha Financial runs grassroots lending, payments and micro-investment for women-led small businesses across Indonesian villages, backed by a branch field network. Hiring is accelerating and dominated by ops, finance, sales and marketing at junior and manager levels, not engineering, so growth is coming from physical branch expansion. The stack pairs XGBoost, LightGBM and scikit-learn credit modeling with a dense security layer (CrowdStrike, SentinelOne, Wazuh, Forcepoint).
Notable leadership hires: Branch Head, Procurement Lead
Amartha Financial is a privately held Indonesian fintech founded in 2010 and headquartered in Jakarta Selatan. It serves women-led micro, small and medium enterprises in rural communities with working capital financing, digital payments and micro-investment products. Credit decisions draw on data-driven scoring, and lending is delivered through a regional branch network organized around borrower groups known as majelis. The company employs 5,001–10,000 people and hires mainly in Indonesia, with some roles in Canada and China. Corporate planning runs on Workday, Anaplan and Adaptive Insights, with infrastructure on AWS and GCP.
Amartha uses Python, Pandas, XGBoost, LightGBM and scikit-learn for modeling, Tableau and Power BI for BI, AWS and GCP for cloud, plus CrowdStrike, SentinelOne, Wazuh and Workday.
Yes. Hiring is accelerating, concentrated in operations, finance, sales and marketing, with leadership roles such as Branch Head and Procurement Lead, mostly in Indonesia.
Current work includes branch expansion such as the Malang region, revamping and mapping majelis borrower groups, fraud detection frameworks, promo abuse risk scoring and an emerging risk framework.
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Amartha Financial's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
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