Staff Data Scientist at GBG | Fraud & AML Systems | Real-time ML, MLOps
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data/AI Scientist with 7+ years of experience building real-time ML systems for fraud and AML detection. Proven track record in designing scalable ML platforms, deploying production-grade models, and enabling financial institutions across APAC to improve fraud detection, compliance, and operational efficiency.
University of Indonesia
Bachelor of Science - B.Sc, Statistics
N/A – Present
GBG Plc
Staff Data Scientist, Fraud APAC
April 1, 2025 – Present
APAC · Hybrid
JULO
Senior Data Scientist
November 1, 2023 – March 1, 2025
Jakarta, Indonesia · Hybrid
Traveloka
Data Scientist - Fraud & Abuse
July 1, 2022 – November 1, 2023
Jakarta, Indonesia
Traveloka
Data Scientist - Credit Risk
August 1, 2020 – July 1, 2022
Jakarta, Indonesia
ADVANCE.AI
Data Scientist - Credit Risk
August 1, 2019 – August 1, 2020
Jakarta, Indonesia
Home Credit Indonesia
Data Analyst - Collection Analytics
September 1, 2018 – August 1, 2019
Greater Jakarta Area, Indonesia
Bukalapak
Data Scientist - Marketing Science
January 1, 2018 – July 1, 2018
Greater Jakarta Area, Indonesia
OVO (PT Visionet Internasional)
Data Engineer
June 1, 2017 – September 1, 2017
Greater Jakarta Area, Indonesia
Upscale 2.0: Data Science
Gojek
June 24, 2026 – Present
All of Machine Learning
Pacmann
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse background across multiple companies (GBG Plc, JULO, Traveloka, ADVANCE.AI, Home Credit Indonesia, Bukalapak, OVO) and industries (Fintech, Travel, E-commerce), demonstrating adaptability and exposure to different organizational cultures. The progression from Data Analyst/Engineer to Staff Data Scientist shows a strong career trajectory and continuous learning. While the target role is 'Analytics Engineer', the candidate's experience is heavily skewed towards Data Science and MLOps, which might require a slight shift in focus towards core data warehousing, ETL/ELT, and data modeling best practices for an Analytics Engineer role. However, the MLOps experience provides a strong foundation for building robust data pipelines.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight leadership in project delivery and cross-functional collaboration (e.g., 'Led end-to-end delivery', 'Partnered cross-functionally'). This suggests strong operational fit and the ability to drive initiatives. The focus on improving efficiency and throughput (e.g., 'improving throughput capacity by >30x', 'reducing model dev cycle by ~30-50%') indicates a results-oriented mindset.