Lead Data Scientist - Big Data and Modelling

Lead Data Scientist - Big Data and Modelling Full-time

Indodana Fintech is an 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 hailed from Silicon Valley Tech companies such as Google, Microsoft, LinkedIn and Sofi as well as Indonesian startups such as Doku, Touchten. We have graduates from well known universities such as Universitas Indonesia, ITB, Stanford, University of Washington, Cornell and many others. We are building a company with the same culture of openness, transparency, drive and meritocracy as Silicon Valley companies. Join us in our cause to build a world class fintech company in Indonesia.

Responsibilities

Lead the

design, development, and deployment

of machine learning models for risk scoring, fraud detection, and behavioural analytics

Drive

feature engineering ,

model training , and

model monitoring pipelines

using large-scale datasets

Build and maintain a scalable

data infrastructure

in collaboration with the Data Engineering team

Manage and mentor a team of data scientists and engineers, ensuring high standards in

model accuracy, interpretability, and governance

Translate complex business problems into

data-driven solutions

and communicate technical insights clearly to stakeholders

Lead

model validation ,

backtesting , and

performance analysis

for new and existing models

Develop and implement

data quality checks , pipelines, and data governance protocols

Qualifications

Bachelor’s or Master’s in Data Science, Computer Science, Applied Mathematics, or related field

3+ years of experience

in data science, machine learning, or risk modeling, ideally in fintech or banking

Strong command of

Python ,

SQL , and big data tools (e.g., Spark, Airflow, Hadoop, AWS/GCP/Databricks)

Experience leading

end-to-end model development

in production environments

Solid understanding of

credit risk ,

fraud analytics , or

financial modelling

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