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# Senior Data Scientist(Japan)

- **Company:** MetLife
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, Microsoft Azure, Cloud Computing, Code Review, Continuous Integration, Data Infrastructure, Python (Programming Language), Machine Learning, Power BI, Large Language Models, Pyspark, Information Technology, Data Analytics, Machine Learning Operations
- **Published:** August 30, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pg4dd035lt

## About the Role

* Business-level Japanese and business communication English.
 * 5+ years of experience in data science / advanced analytics with delivered business results.
 * Experience leading data science projects end-to-end (from idea to delivery).
 * Strong Python programming skills and strong code review skills.
 * GenAI / LLM experience.
 * Azure or similar cloud experience (building and/or deploying solutions).
 * People Management experience (leading a team, coaching, supporting performance).
 * Willing to learn, take on new challenges, and adapt to change.
 * Strong teamwork and collaboration skills.

Education

Bachelor's degree in computer science, information technology or equivalent educational qualification

Good To Have

 * Financial services experience (insurance experience is a plus).
 * MLOps experience (CI/CD, deployment, monitoring, model lifecycle).
 * Power BI experience.
 * PySpark experience.

## Description

The Senior Data Scientist will drive innovative approaches to understanding, interacting, and optimizing customer engagement by leveraging advanced analytics to derive actionable business insights. The successful candidate will work closely with business stakeholders to understand their requirements and the broader business context. This role entails leading data analytics initiatives from conception through implementation to delivery., * Work with business teams to understand goals, define success measures, and turn needs into clear analytics tasks.

 * Lead data science projects end-to-end: define the problem, analyze data, build models, test results, and deliver.
 * Build and improve machine learning and analytics solutions that support business goals.
 * Manage a team of data scientists and vendor resources, provide coaching, feedback.
 * Review code and help the team write clean, reliable Python.
 * Work with the data platform and IT teams to plan delivery, manage dependencies, and remove blockers.
 * Deliver solutions on Azure (or similar cloud) with support from engineering teams.
 * Create clear documentation and simple updates for stakeholders and leaders.
 * Use AI responsibly and follow company policies and compliance requirements.


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