farhanrn

Data Scientist | Risk & Fraud Analytics Specialist

Data Analyst and Risk Management professional with experience in financial auditing, fraud detection, compliance monitoring, and data analytics. At PT Mandiri Utama Finance, I managed and audited high-volume financial datasets, implemented early warning systems, and identified fraud patterns, transaction anomalies, and compliance risks.

Beyond finance, I led a 14-member engineering team in developing machine learning solutions, mentored aspiring data analysts in Python and SQL, and contributed to peer-reviewed research at BRIN. My technical expertise includes Python, SQL, Power BI, Excel, predictive modeling, and anomaly detection.

I am passionate about applying data-driven risk management and fraud analytics to the Web3 ecosystem. Currently seeking remote opportunities as a Fraud Analytics Specialist, Risk & Compliance Data Scientist, or Blockchain/On-Chain Data Analyst, helping exchanges, protocols, and fintech platforms detect suspicious activity, strengthen compliance frameworks, and secure digital assets.

Experience: 2 years

Yearly salary: $30,000

Hourly rate: $15

Nationality: 🇮🇩 Indonesia

Residency: 🇮🇩 Indonesia

Experience

Quality Control Assurance

Mandiri Utama Finance

2025 - 2026

Served as a Quality Control Assurance professional, leveraging data-driven risk management and analytical reporting to safeguard corporate operations and compliance frameworks. Responsible for implementing early warning systems and monthly risk monitoring across four branch offices to proactively identify and mitigate operational, credit, and compliance risks. Actively managed and analyzed high-volume operational datasets using multi-channel verification methodologies—including on-desk reviews, onsite verifications, and telephone validation—to pinpoint operational deviations, compliance gaps, and critical anomaly indicators. Systematically evaluated quality control findings and structured complex risk issues into defined categories, including Competence, Compliance, and Integrity, transforming raw audit data into actionable insights for corrective action and process optimization.

Data Analyst Mentor

Screenesia

2024 - 2025

Acted as a Data Analyst Mentor, guiding aspiring data professionals through the core methodologies of data validation, cleansing, and comprehensive reporting. Developed and delivered structured mentorship focused on hands-on technical execution using Python, SQL, and Power BI. Empowered mentees to design, build, and optimize interactive data dashboards, fostering their ability to extract critical business intelligence and effectively communicate data-driven insights to support strategic decision-making processes.

Research Assistant

BRIN

2023 - 2024

Worked as a Research Assistant for the "Riset dan Inovasi untuk Indonesia Maju" (RIIM) Batch 4 program, contributing to high-level academic and applied scientific exploration. Conducted a rigorous and systematic literature review analyzing over 50 comprehensive research studies to evaluate the effectiveness of metaheuristic-based feature selection methods within predictive healthcare modeling. Successfully identified critical methodological trends and research gaps in the existing literature, directly contributing to a technical manuscript published in a peer-reviewed scientific journal

Machine Learning Engineer

GoDentist

2023 - 2024

Led a cross-functional technical team of 14 members as a Machine Learning Engineer to pioneer the development of an advanced, data-driven classification system. Directed the end-to-end data pipeline operations, which included the preparation, curation, and optimization of a high-quality dataset consisting of over 6,900 images. Coordinated cross-functional collaboration between cloud infrastructure and backend engineering teams to ensure seamless model integration, scalability, and robust system architecture

Data Annotator

Qlue Smart City

2021 - 2022

Contributed to smart city monitoring infrastructure as a Data Annotator, focusing on computer vision and automated detection systems. Successfully processed and annotated a high volume of over 22,000 images dedicated to crucial urban monitoring projects, including road damage assessment, license plate recognition, and vehicle detection . Utilized CVAT to maintain strict data quality and tagging accuracy, directly supporting the optimization and training precision of machine learning models used in smart city systems.

Skills

analyst

communications

data viz

machine-learning

python

quantitative

sql

operations

english

indonesian

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