Data Scientist

We are looking for an Automation Data Scientist to design, build, and productionize machine learning, statistical, and LLM-based automation solutions for DANA's KYB merchant onboarding and merchant risk decisioning. This role will help transform manual verification and review processes into automated, monitored, and auditable decision-making systems, enabling the business to scale merchant onboarding, improve operational efficiency, and reduce fraud and compliance risks through data-driven intelligence.
Responsibilities
Design, build, and deploy machine learning, statistical, and LLM-based solutions for merchant risk detection and KYB automation.
Develop automated verification, classification, and decisioning models to improve onboarding efficiency and reduce manual reviews.
Build and maintain scalable end-to-end ML pipelines, including feature engineering, model deployment, monitoring, and retraining.
Monitor model performance, data quality, and governance to ensure reliable, auditable, and compliant decision-making.
Partner with Product, Engineering, Risk, Compliance, and Merchant Operations to translate business requirements into data-driven automation solutions.
Conduct experiments and optimize decision thresholds to balance fraud prevention, merchant experience, and business growth.
Communicate insights, model performance, and recommendations effectively to technical and non-technical stakeholders while ensuring compliance with data privacy and governance standards.
Keeping up to date with the latest technology trends in data science, machine learning, and large language models, and actively pursuing continuous learning opportunities.
Requirements
Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
2+ years of practical experience as a Data Scientist with hands-on experience delivering ML models into production.
Strong knowledge of machine learning, statistical modeling, and practical experience with NLP, LLMs, computer vision, clustering, and tree-based algorithms.
Proficient in Python (pandas, NumPy, scikit-learn, TensorFlow/PyTorch) and strong SQL, with experience using ML and data engineering tools such as Spark, Airflow, and MLflow.
Experience building scalable data pipelines, feature engineering, data transformation, and ensuring data quality for analytical and production use.
Excellent programming skills with clean, modular code and software engineering best practices (Git, unit testing, code reviews, and CI/CD).
Strong problem-solving skills with a data-driven mindset and the ability to translate business needs into AI/ML solutions.
Excellent written and verbal communication skills, with the ability to present complex technical concepts to both technical and business stakeholders.
Self-starter with the ability to work independently and collaborate effectively across Product, Engineering, Risk, and Compliance teams.
Proficient in English and Bahasa Indonesia.
Experience in fintech, payments, digital banking, or merchant risk, KYC/KYB, AML, or fraud detection.
Familiarity with MLOps, cloud platforms, API development, and containerization.
Experience with graph analytics, multilingual NLP/LLMs, and Indonesian regulatory requirements (UU PDP, BI/OJK).
Passion for leveraging AI and automation to solve complex business problems.