Senior Data Scientist - Lending

Lever, Inc.; Jakarta Pusat; On-site; IDR 300,000,000 - 600,000,000; Full time

Job summary

GoTo Group is seeking a Data Scientist to lead the development, evaluation, and monitoring of credit risk models for GoPay lending products in Indonesia. You will own the ML lifecycle, from conception to deployment, and work with cross-functional teams to translate business challenges into data-driven solutions.

You will apply advanced ML techniques to optimize lending decisions, manage risk, and support financial inclusion in the region.

Qualifications

• Bachelor’s degree or above in science/engineering related fields.
• At least 3 years of hands-on experience building, evaluating, and monitoring credit risk models.
• Excellent understanding of machine learning techniques and algorithms.
• Proficient in Python, SQL, and UNIX Shell.
• Able to translate business concerns into technical problems and solutions.
• Self-driven with ownership in a fast-paced environment.
• Strong communication and ability to present technical concepts to non-technical audiences.

Responsibilities

• Drive end-to-end impact: own the ML lifecycle from conception to deployment and monitoring.
• Innovate credit risk strategy by developing advanced consumer credit risk models.
• Collaborate with product and business teams to translate challenges into scalable data solutions.
• Champion technical excellence with robust model evaluation and clear documentation.

Skills

Python

SQL

UNIX Shell

Machine Learning

Statistical Analysis

Communication

Education

Bachelor's degree or above in science/engineering

Job description

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.

About the Team

Our team leverages big data from the GoTo universe, as well as external data, to build various predictive models to support the risk strategy team in real-time credit underwriting and management of the customer lifecycle Cicil (BNPL) and Pinjam (cash loans) products. As our model scores are key inputs to risk decisioning (e.g. approval/rejection of loans, credit limit adjustments), we are also able to see the direct impact of our models on the business and our customers.

We are a growing team and are constantly looking for opportunities to use data science to enhance our credit and fraud risk management capabilities. We are focused on growth and efficiency. We are all about open knowledge sharing and self-improvement. We believe that "Data Science is a team sport."

About GoTo Group

GoTo is the largest digital ecosystem in Indonesia. GoTo's mission is to 'empower progress' by offering technology infrastructure and solutions that help everyone to access and thrive in the digital economy.

The GoTo ecosystem provides a wide range of services, including mobility, delivery, payments, financial services, and technology solutions for merchants. The ecosystem also provides e-commerce services through Tokopedia and banking services through its partnership with Bank Jago.

About Gojek

Gojek is Southeast Asia's leading on-demand platform and pioneer of the multi-service ecosystem with over 2.5 million driver partners across the regions offering a wide range of services such as transportation, food delivery, logistics and more. With its mission to create impact at scale, Gojek is committed to resolving consumer problems and raising standards of living by connecting consumers to the best providers of goods and services in the market.

About GoTo Financial

GoTo Financial accelerates financial inclusion through its leading financial services and merchants solutions. Its consumer services include GoPay and GoPayLater and serve businesses of all sizes through Midtrans, Moka, GoBiz Plus, GoBiz, and Selly. With its trusted and inclusive ecosystem of products, GoTo Financial is open to new growth opportunities and aims to empower everyone to Make It Happen, Make It Together, Make It Last.