【TW Life】Supervisor, Data Science Dept.

• 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.

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.

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