Data professional with 10+ years of experience in analytics, machine learning, experimentation, and data product development across fintech, insurance, and e-commerce. I enjoy turning messy business problems into practical, scalable solutions — whether that’s building risk and fraud models, designing A/B tests, automating ML workflows, or creating data products that drive real business impact. My work has helped improve revenue, optimize operations, and prevent fraud at companies like Traveloka and JULO.
I’m hands-on, business-oriented, and comfortable working independently in remote environments while collaborating closely with cross-functional teams. Strong in Python, SQL, statistics, experimentation, and machine learning, with a focus on building solutions that are both technically solid and practical for business needs. Currently open to remote freelance and contract opportunities in data analytics, data science, and analytics engineering.
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Designed and implemented an automated end-to-end machine learning training and experiment tracking pipeline using MLflow, enabling reproducible model development, centralized experiment logging, and streamlined deployment workflows. The project automated key stages including data preprocessing, model training, hyperparameter configuration, metric evaluation, artifact/version tracking, and model registration, improving scalability, consistency, and monitoring across the ML development lifecycle while reducing manual operational effort.
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