Lead Data Scientist - Lending

Go To Group; Jakarta Pusat; Sur place; IDR 900 000 000 - 1 300 000 000; Plein temps

Résumé du poste

Go To Group mengundang Anda sebagai Lead Data Scientist - Lending untuk memimpin tim data science dalam pembangunan, evaluasi, dan pemantauan model risiko kredit untuk produk pinjaman konsumen dan merchant di Indonesia. Peran ini akan memanfaatkan data internal GoTo serta data pihak ketiga untuk meningkatkan inklusi keuangan.

Anda akan membentuk tim, membangun model kredit risiko, dan menyajikan rekomendasi berbasis data untuk keputusan underwriting dan manajemen siklus hidup pelanggan Cicil dan

Qualifications

• Gelar sarjana atau lebih tinggi di bidang sains/rekayasa (statistik, matematika, fisika, CS, dll).
• Minimal 6–7 tahun pengalaman langsung membangun, mengevaluasi, dan memantau model risiko.
• Pemahaman yang kuat tentang metode ML dan algoritme.
• Mahir menggunakan Python, SQL, dan UNIX Shell.
• Mampu mengubah masalah bisnis menjadi masalah teknis berbasis data dan statistik.
• Mandiri, inovatif, dan mampu bekerja di lingkungan cepat.
• Keterampilan komunikasi yang baik untuk menjelaskan konsep teknis secara sederhana.

Responsabilités

• Memimpin inisiatif pemodelan end-to-end serta menentukan metrik bisnis.
• Bekerjasama dengan tim bisnis/produk untuk mendefinisikan, prototyping, dan mengimplementasikan model DS.
• Membangun tim data science yang berkinerja tinggi dan mengembangkan budaya kolaborasi.
• Mengawasi pengembangan model risiko konsumen dan analisis statistik untuk optimasi keputusan.

Connaissances

Experiencing risk models

Python

SQL

UNIX Shell

Machine Learning

Communication skills

Formation

Bachelor degree or above in STEM

Outils

Python

SQL

UNIX Shell

Description du poste

Lead Data Scientist - Lending

Perusahaan : Go To Group
Jenis Pekerjaan : Full-Time
Lokasi: Jakarta, Indonesia

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

• 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.

What You Will Need

• 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.

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.

Tentang Perusahaan

Go To Group

Kami adalah perusahaan teknologi nomor 1 di Indonesia. GoTo berdedikasi untuk menciptakan dampak sosial berskala besar di manapun kami beroperasi.