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🏦🌐 臺灣的大型金融控股公司 🏛️🌐🏦 參與集團 新技術導入 AI 技術開發與應用 與 商務等數據洞察與業務應用探索 AI 技術開發與應用：負責大語言模型調優技術開發，因應不同子公司業務需

About the Role Gojek is a data-driven organization. Data has become the most critical part of its strategy to become the market leader through innovations and service excellence. As a Data Warehouse Developer, you’ll take a critical part in developing & maintaining our large-scale data environments that will be valuable for our main users to generate business insights, decision-making, deep analysis, and even data science products. You’ll have the opportunity to work with

We are looking for a data scientist to join our Data Science team at GoPay - you will create models which help grow the customer base and transactions in GoPay. You will work closely with the business, product and engineering stakeholders to identify and solve some of the most challenging business problems in the payments space. You will have the opportunity to work in a fast-paced environment in a highly cross-functional team and leverage our robust data

As a senior data scientist in the GoTo Risk Data Science team, you will develop data science models for On-Demand Services (aka Gojek). You will have the opportunity to work with large-scale data to derive new intelligence and use cutting-edge data science techniques. You will partner with Risk, product, and engineering stakeholders to identify and solve some of the most impactful and stimulating business problems. You will work in a fast-paced environment with

for Food & Consumer Risk you will be part of a team that identifies Risk problems and leads end-to-end solutions for all Gojek’s operating countries. You will be protecting Gojek from fraud losses, while at the same time protecting Gojek’s Consumers’ experience and safety at the platform. You will have the opportunity to work in a fast-paced environment in a highly cross-functional organization that includes wider Risk management, Data Science, Engineering, Product Man

In this role, you will be an integral player within the GoFinance Data Science team based in Singapore. You will take the wheel in overseeing building, evaluating, and monitoring credit risk models for a variety of consumer and merchant lending products GTF offers in Indonesia. Your responsibilities will include enhancing our credit risk models through heavy feature engineering of GoTo data as well as data purchased from third-party data vendors, and ensuring that they are stable and

About the Role Data Scientists want to spend their time exploring data, crafting the right features and optimising their models… so far so good. Production requires a lot more though. What about the data pipelines? Scaling up infrastructure based on demand? Running experiments at scale? Feature data consistency? This is where you come in as a Software Engineer for Gojek’s ML platform. Most companies embed ML engineers in data science teams to solve these problems.

Data has become the most critical part for Gojek to become the market leader through innovations & service excellences. As a Data Warehouse Developer, you’ll take a critical part in developing & maintaining our large scale data environments that will be valuable for our main users to generate business insights, decision making, deep analysis, even data science products. You’ll have the opportunity to work with multiple cross functional teams, such as Product Managers, BI Analyst, Product Enginee

Minimum qualifications: Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience 3 years of experience with statistical data analysis, data mining, and querying (e.g., SQL). 1 year of experience managing analytical projects Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 5 years of experience with analysis applications (

Minimum qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, a related quantitative field, or equivalent practical experience. 5 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL). Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 8 years of work exp