About the role
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.
You'll be working on:
- 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.
Qualifications:
- 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.
