Senior Credit Risk ML Scientist - Lending Growth

GoPay; Jakarta Pusat; Hybrid; IDR 334,800,000 - 613,800,000; Full time

Job summary

GoPay Data Science team in Jakarta is seeking a hands-on Data Scientist to build, evaluate, and monitor credit risk models for consumer and merchant lending in Indonesia. You will own the ML lifecycle and collaborate with product and business to translate challenges into scalable solutions.

We require a strong background in statistics, ML, Python, SQL, and UNIX, plus at least 3 years of practical experience in credit risk modeling.

Qualifications

• Bachelor degree or above in statistics, mathematics, physics, computer science or related fields.
• At least 3 years of hands-on experience in building, evaluating, and monitoring credit risk models.
• Strong understanding of machine learning techniques and algorithms.
• Proficient in Python, SQL, and UNIX Shell.
• Able to translate business concerns into technical problems solvable with data and math.
• Self-driven with ownership mindset in a fast-paced environment.
• Strong communication skills and ability to present concepts to non-technical audiences.
• Ability to document models clearly and support recommendations with research and data.

Responsibilities

• Own the machine learning lifecycle from conceptualization to deployment and monitoring.
• Lead development of advanced consumer credit risk models to optimize lending decisions.
• Collaborate with product and business teams to translate challenges into scalable data solutions.
• Set standards for model evaluation and documentation and communicate insights to leadership.

Skills

Credit risk modeling

Machine learning techniques

Python

SQL

UNIX Shell

Communication

Education

Bachelor degree or above in statistics, mathematics, physics, computer science

Tools

UNIX Shell

Data pipelines

SQL

Job description

GoPay Data Science team in Jakarta is seeking a hands-on Data Scientist to build, evaluate, and monitor credit risk models for consumer and merchant lending in Indonesia. You will own the ML lifecycle and collaborate with product and business to translate challenges into scalable solutions.

We require a strong background in statistics, ML, Python, SQL, and UNIX, plus at least 3 years of practical experience in credit risk modeling.