The Role
Lead development of personalization and recommendation systems using large-scale transactional data. Define model strategy, build and deploy scalable ML pipelines, run experiments to measure impact, mentor data scientists, and collaborate with Product and Engineering to drive customer engagement and transactions.
Summary Generated by Built In
About the Role
Develop and optimize personalization and recommendation models to deliver relevant offers, merchants, and experiences to GoPay users. Apply a range of DS techniques—such as collaborative filtering, ranking models, embeddings, and graph-based methods to improve discovery and user engagement. Work closely with product and engineering teams to design, test, and deploy end-to-end ML pipelines in production. Prototype rapidly, run A/B tests, and analyze online/offline metrics (CTR, conversion rate, NDCG, recall@k, etc.) to evaluate model performance and business impact. Leverage large-scale behavioral and transactional data to uncover insights and guide feature design and personalization strategies. Contribute to continuous improvement by monitoring model performance, identifying data or algorithmic gaps, and iterating based on real-world feedback. Collaborate cross-functionally with other data scientists and engineers to share best practices, improve our personalization infrastructure, and align with GoTo’s broader personalization roadmap.
What You Will Do
- Work as part of a cross-functional team of engineers, product managers and business analysts to build data science solutions that build customer engagement and help grow GoPay’s customer base and transactions.
- Rapidly prototype data science solutions and be involved in product and feature discussions
- Analyze large volume data and generate insights which will be actionable.
- Own end-to-end solutioning, from formulating the technical problem to deployment (along with engineers) of the solution
- Participate in internal and external conferences and workshops.
- Design and implement algorithms for search, recommendation, or advertising systems to drive discovery and conversion across Goto products.
- Build advanced user behaviour models and query/assortment understanding models using LLMs and LLVMs to improve matching accuracy between users, queries, and items across search and recommendation systems.
- Collaborate with product, engineering, and business-facing data science teams to define problems, run experiments, and deploy solutions at scale.
What You Will Need
- 6–8 years of relevant experience in applied data science or machine learning roles.
- Proficiency in Python, and familiarity with ML frameworks such as Scikit-learn, TensorFlow, or PyTorch.
- Solid understanding of ML fundamentals including supervised learning, ranking, embeddings, and evaluation metrics.
- Experience working with large-scale datasets using platforms such as Spark, MaxCompute (MC), or other distributed data environments.
- Strong analytical and problem-solving skills, with the ability to translate complex data insights into actionable recommendations.
- Good communication skills to engage with cross-functional partners and present results clearly.
- Master’s or Ph.D. in a quantitative discipline (e.g., Computer Science, Statistics, Applied Mathematics, or related field) is a plus.
- Hands-on experience with search/ recommendation/ads systems, with proven improvements to ranking, retrieval, or ad targeting models.
- Familiarity with LLMs and/or LLVMs, with experience integrating them into search or recommendation pipelines a strong plus.
- Demonstrated ability to innovate with new algorithms or tools and drive measurable impact, especially making use of Large language Models (LLMs) and Large Language and Vision models (LLVMs) in search modeling or recommendation modeling
- Strong product intuition and ability to reason from user behavior data and traffic patterns.
- Good communication skills in English, both written and verbal.
- Self-motivated, curious, and excited by the opportunity to build high-impact systems quickly.
About the Team
GoPay Data Science team builds critical ML components/models which go into the engineering systems which make GoPay a safe, trusted and fun way to do payments. Our team members come from varied backgrounds, and bring with them a wide set of skills (mathematics, statistics, machine learning, deep learning etc) which we use some of the toughest business problems in GoPay. We are enthusiastic about both data science techniques and methods, as well as the business impact of our models, and have numerous internal forums where sharing, discussions and presentations by the team members happen.
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.
GoTo and its business units, including Gojek and GoToFinancial ("GoTo") only post job opportunities on our official channels on our respective company websites and on LinkedIn. GoTo is not liable for any job postings or job offers that did not originate from us. You should conduct your own due diligence to prevent being victims of any fake job scams, if they did not originate from GoTo's official recruitment channels.
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Skills Required
- 6-8 years of relevant experience in applied data science or machine learning roles
- Proficiency in Python
- Familiarity with ML frameworks such as Scikit-learn, TensorFlow, or PyTorch
- Solid understanding of ML fundamentals including supervised learning, ranking, embeddings, and evaluation metrics
- Hands-on experience in recommender systems, personalization, search, or ranking models
- Experience working with large-scale datasets using platforms such as Spark, MaxCompute (MC), or other distributed data environments
- Strong analytical and problem-solving skills
- Good communication skills to engage with cross-functional partners
- Master's or Ph.D. in a quantitative discipline (e.g., Computer Science, Statistics, Applied Mathematics) is a plus
GoTo Group Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about GoTo Group and has not been reviewed or approved by GoTo Group.
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Fair & Transparent Compensation — Pay is considered competitive to above market for many corporate roles across core entities such as Gojek, Tokopedia, and GoTo Financial. Base pay is often characterized as solid or above market in Indonesia tech roles.
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Healthcare Strength — Medical coverage is characterized as strong in Indonesia and often extends to spouses and children. Company materials also highlight wellness support, parental insurance, and mental‑health counseling for employees and families.
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Leave & Time Off Breadth — Leave programs are described as generous, including maternity, paternity, and other special leave types at Tokopedia. Broader time‑off and flexibility practices are portrayed as supportive across corporate roles.
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The Company
What We Do
GoTo is the largest technology group in Indonesia, combining on-demand, e-commerce and financial services through the Gojek, Tokopedia and GoTo Financial brands. It is the first platform in Southeast Asia to host these three essential use cases in one ecosystem, capturing a majority of Indonesian consumer household expenditure. GoTo’s mission is to “Empower Progress” by offering an unparalleled selection of goods and services through a comprehensive merchant and partner network and promoting financial inclusion through its leading payments and financial services business.
