- Apply machine learning and analytics to drive business value and revenue growth.
- Collect, clean, and analyze structured and unstructured data from various sources.
- Perform exploratory data analysis and visualize results using standard tools (e.g., Tableau).
- Develop, implement, and optimize machine learning models for business applications (e.g., marketing targeting, campaign effectiveness, product optimization).
- Collaborate with teams and business stakeholders to deliver solutions and support decision-making.
- Communicate findings and analytic solutions to stakeholders, document processes, and present results clearly.
- Stay updated with the latest trends, tools, and technical knowledge in data science and related industries.
- Work in a dynamic, project-oriented environment with multiple concurrent tasks.
Qualifications
Must:
- 3+ years’ experience in Data Science using Python/SAS.
- Strong problem-solving skills in ML modeling.
- Advanced hands-on experience in predictive modeling, data mining, and statistical analysis.
- Master’s degree or above in computer science, statistics, applied mathematics, or related discipline.
- Good communication and teamwork skills.
Plus:
- Domain knowledge in life insurance, banking, healthcare, or digital marketing.
- Experience with data visualization tools (e.g., Tableau, Matlab).
- Familiarity with MLOps.
- Strong English ability.
- Experience in cloud environments (e.g., Azure, AWS).
- Professional ML-related certifications (e.g., Azure Data Scientist Associate, AWS Machine Learning).
- Publications/patents in ML fields.
- Cross-functional project experience.
Personal Competencies:
- Good communication and negotiation skills.
- Ability to handle pressure and meet deadlines.
- Enthusiasm, personal drive, willingness to learn, and attention to detail.
★Recruitment Process Notice
• Please note that interview coordination for the next stage will be handled by our offshore Service Hub.
• All interview-related communications — including availability confirmation and interview invitations — will be conducted via email only.
• As phone contact is not available at this stage, kindly check your email regularly (including spam or junk folders) to avoid missing important updates.
★Learn more about Chubb Life Taiwan's culture and workplace
• [開箱影片] 走進我們的辦公室，認識工作環境、福利與文化
• [Podcast] 探索我們如何打造支持成長與創新的職場
