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Salary
≈ $15k – $39k per year (Estimated)
Location
In office (Jakarta)
Seniority
Senior · 3+ years exp

Confirmed on the employer's own hiring board on Oct 29, 2026. First seen by Alion on Jul 1, 2026. GoTo Group scores A on the Alion truth index.

Overview
Company
Impact
Profile match
GoTo (PT GoTo Gojek Tokopedia Tbk) is Indonesia's largest digital ecosystem, formed in 2021 through the historic merger of ride-hailing pioneer Gojek and e-commerce giant Tokopedia. Headquartered in Jakarta and listed on the Indonesia Stock Exchange (IDX: GOTO), GoTo integrates three primary digital business pillars across Southeast Asia.

About the Role

In this role, you will be an integral player within Data Science team based on Jakarta. You will take the wheel in building, evaluating, and monitoring credit risk models for a variety of consumer and merchant lending products GoPay offers in Indonesia. Your responsibilities will include enhancing our credit risk models by leveraging innovative and cutting-edge algorithms on GoTo data and third-party data vendors. Most importantly, your efforts will work to bring wider financial inclusion to more people in the region and beyond.

What You Will Do

  • Drive End-to-End Impact: Take complete ownership of the machine learning lifecycle. You will conceptualize, build, deploy, and monitor data models that directly influence key business metrics and bottom-line results.
  • Innovate Credit Risk Strategy: Lead the development of advanced consumer credit risk models. Apply rigorous statistical analysis and ML techniques to optimize lending decisions, balance risk, and fuel sustainable business growth.
  • Partner with Product & Business: Act as a strategic bridge between data and business strategy. Collaborate closely with cross-functional teams to translate ambiguous business challenges into scalable, production-ready data science solutions.
  • Champion Technical Excellence: Set the standard for robust model evaluation and clear documentation. You will advocate for data science best practices and distill complex technical concepts into actionable insights for non-technical leadership.

What You Will Need

  • Bachelor degree or above in science and engineering related majors such as statistics, mathematics, physics, computer science, etc.
  • At least 3 years of hands-on experience in building, evaluating, and monitoring credit risk models.
  • Excellent understanding of machine learning techniques and algorithms.
  • Comfortable using Python, SQL, and UNIX Shell.
  • Understand business concerns and formulate them as technical problems that can be solved using data and math/stats/ML.
  • Self-driven and entrepreneurial with a strong sense of ownership, and thrive in a fast-paced environment.
  • Good communication skills and ability to present technical concepts to a non-technical audience.
  • Able to write model documentation clearly and concisely and support recommendations with research and data.
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