Lead Data Scientist - Lending

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.

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.”

* Own end-to-end modeling modeling initiatives and business outcomes / metrics.

* Work with the business/product team in defining, prototyping, and implementing data science models and other supporting DS initiatives.

* Recruit, mentor, and develop a high-performing data science team, fostering a culture of collaboration and innovation.

* Oversee the development of consumer credit risk models and statistical analyses to optimize decision-making and business outcomes.

* Bachelor degree or above in science and engineering related majors such as statistics, mathematics, physics, computer science, etc.

* At least 6-7 years of hands-on experience in building, evaluating, and monitoring 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.