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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

Minimum qualifications: Master's degree in a STEM field or equivalent practical experience. 4 years of industry or PhD Data Science experience. Experience in causal inference, A/B testing, statistical modeling, or Machine Learning (ML). Experience with programming in SQL and Python, leveraging ML or statistical libraries (e.g. TensorFlow, Scikit-learn, XGBoost, Keras, Pandas). Preferred qualifications: PhD in a STEM field. Publications related to Data Science, posters or presentations in Artific

About the Role Gojek is a data-driven organisation. 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

Gojek is a data driven organization. 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

What You Will Do Translate business concerns into technical problems that can be addressed using data science and machine learning techniques. Collaborate with product managers, machine learning engineers, and business users to develop and deploy data science solutions. Prototype and deploy data science models, ensuring they are scalable and maintainable in a production environment. Partner with business teams to continuously improve systems to meet Gojek’s evolving needs. Analyze large datasets

公司介紹： 我們的客戶是一家領先的金融科技公司，致力於通過數位、數據和技術推動整體轉型。公司正在積極打造數據驅動文化，以成為提供卓越金融服務的科技公司為目標。公司環境開放創新

The Role: We are seeking an exceptionally talented data scientist with strong modeling and programming skills to join our team. In this role, you will work closely with data science team and technologists across the firm to develop appropriate features and metrics for data processing. Perform analysis and generate models of financial datasets using machine learning techniques Process, clean and verify the integrity of unstructured data and turn data into valuable insights Develop and create data

公司介紹 金融保險業(產險)，在台成立60年，為日本在台子公司。2022 亞洲最佳企業雇主獎， 視員工為珍貴資產，對於幸福職場的營造及專業人才的育成不遺餘力，2022年度首次參賽即獲《HR Asia》(亞洲權威性

＊請至 【 https://mobagel.typeform.com/to/ojShbwVv 】 投遞履歷，謝謝你的協助＊ Job Function -Analyze and interpret large datasets using Pandas, NumPy, and Scikit-Learn -Develop and deploy predictive models to solve complex business problems -Optimize data pipelines and ETL processes for efficiency -Collaborate with engineering teams to integrate data science solutions into production systems Your Impact -Drive data-informed decision-making across the organization -Deliver insights