【TW Life】Supervisor, Data Science Dept.

Taipei City, Taiwan

Pay: Pay not listed
Work setting: Not stated
Employment: Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

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What you’ll work on

Full posting

Develop, implement and optimize machine learning models for business uses
Collect, clean and analyze structured and unstructured data
Run exploratory data analysis and visualize results in tools like Tableau
Communicate findings and document analytic solutions for stakeholders
Work on multiple concurrent projects in a dynamic environment

From the employer’s posting

Develop, implement, and optimize machine learning models for business applications

Collect, clean, and analyze structured and unstructured data from various sources

Perform exploratory data analysis and visualize results using standard tools (e.g., Tableau)

Communicate findings and analytic solutions to stakeholders, document processes, and present results clearly

Work in a dynamic, project-oriented environment with multiple concurrent tasks

What you’ll bring

All qualifications

Core experience

3+ years of data science experience using Python or SAS
Advanced hands-on experience in predictive modeling, data mining and statistical analysis
Master's degree or above in computer science, statistics, applied math or related field
Strong problem-solving skills in ML modeling
Good communication and teamwork skills

Qualification wording

3+ years’ experience in Data Science using Python/SAS

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

Strong problem-solving skills in ML modeling

Good communication and teamwork skills

Education & alternatives

- 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.

Tools in this posting

MATLAB
Python
SAS
AWS
Azure
Tableau

Source

- Domain knowledge in life insurance, banking, healthcare, or digital marketing. - Experience with data visualization tools (e.g., Tableau, Matlab). - Familiarity with MLOps.

Must: - 3+ years’ experience in Data Science using Python/SAS. - Strong problem-solving skills in ML modeling.

- Strong English ability. - Experience in cloud environments (e.g., Azure, AWS). - Professional ML-related certifications (e.g., Azure Data Scientist Associate, AWS Machine Learning).

- 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.

- 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).

Posting record

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Open 6 monthsWe first saw this posting 186 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records: Live
First seen by us: Apr 26, 2026 · 186 days ago
Recorded sightings: 442
Last seen by us: Oct 30, 2026
Employer says posted: Feb 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

Your next step

Have your resume and examples of relevant work ready.
Check the listed location, eligibility and core experience before starting.
Ask the employer about the pay range before committing time to the process.

Complete your application on fa-ewgu-saasfaprod1.fa.ocs.oraclecloud.com. The employer’s form will show what is required.

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Job description

View original posting ↗

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.

★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

Source details

View original posting ↗