Senior Data Scientist

PT Artajasa Pembayaran Elektronis (ATM Bersama) is one of Indonesia's leading payment infrastructure providers, delivering secure, reliable, and high-availability transaction services for banks and financial institutions. As a key enabler of the national payment ecosystem, Artajasa operates mission-critical platforms that support interbank connectivity, fund transfers, switching, clearing, and settlement services across Indonesia. Through continuous innovation and technology advancement, Artajasa is committed to building scalable and resilient payment solutions that support the future of digital finance.

We are seeking Senior Data Scientist to develop data-driven solutions that support business growth, operational efficiency, and innovation across the payment ecosystem. This role will work with large-scale transaction data to develop advanced analytics, predictive models, and machine learning solutions that generate actionable business insights.

• Design, build, and deploy data models that turn company data assets into new products, services, and revenue streams (e.g. scoring models, data products, APIs, insights as a service).
• Identify and evaluate opportunities to create business value from data, in collaboration with product, business, and engineering teams.
• Develop end-to-end ML/statistical pipelines: data exploration, feature engineering, model development, validation, and deployment.
• Translate business requirements into measurable modeling objectives and success metrics (e.g. revenue impact, model accuracy, adoption).
• Monitor and maintain model performance in production; retrain or improve models as needed.
• Ensure data quality, governance, and compliance (privacy, security) throughout the modeling lifecycle.
• Communicate findings and model results clearly to both technical and non-technical stakeholders.
• Work independently with minimum supervision, able to plan, prioritize, and execute projects end to end.
• Mentor junior data scientists/analysts as needed (for senior-level candidates).

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or related field.
• Minimum 5 years of experience in data science/machine learning roles, with a track record of deploying models into production.
• Strong proficiency in Python and/or R, SQL, and ML frameworks (scikit-learn, XGBoost, Tensor Flow/PyTorch, etc.).
• Solid understanding of statistical modeling, machine learning algorithms, and model evaluation techniques.
• Experience working with large-scale/big data tools (Spark, Hadoop, cloud platforms such as AWS/GCP/Azure) is a plus.
• Experience building data-driven products or revenue-generating models is strongly preferred.
• Fraud modeling/fraud detection experience is a strong plus (anomaly detection, risk scoring, transaction monitoring).
• Proven ability to work independently, take ownership of projects and deliver results with minimum supervision.
• Strong business acumen, with the ability to connect technical modeling work to business and revenue outcomes.
• Excellent communication and stakeholder management skills.