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# Tech Bilingual Data Scientist (Global AI Company)Machine Learning Engineer | Up to ¥14M | Tokyo Hybrid

- **Company:** TechJobLinks
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Data Analysis, Big Data, Cluster Analysis, Data Cleansing, Linux, Github, Python (Programming Language), Machine Learning, Natural Language Processing, NumPy, Recommender Systems, Software Engineering, SQL Databases, Feature Engineering, Pytorch, Large Language Models, Deep Learning, Model Validation, Generative AI, Scikit Learn, Machine Learning Operations, Software Library, Docker
- **Published:** October 29, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pvblr923i1

## About the Role

* 4+ years of professional experience in Data Science.
 * Strong knowledge of machine learning, statistical modeling, and predictive analytics.
 * Professional experience using Python and SQL.
 * Experience with machine learning libraries such as Scikit-learn, NumPy, or PyTorch.
 * Experience working with structured data, including tabular and time-series datasets.
 * Hands-on experience with classification, regression, clustering, and predictive modeling.
 * Experience across the complete machine learning lifecycle, including model development, deployment, and production maintenance.
 * Knowledge of feature engineering, model evaluation, cross-validation, and A/B testing.
 * Familiarity with Linux, Git/GitHub, Docker, and CI/CD environments.
 * Experience collaborating with software engineers to integrate ML models into production systems.
 * Business-level Japanese communication skills.
 * Willingness to communicate and collaborate in English within an international engineering environment.

Ideal Candidate

We are looking for a hands-on Data Scientist or Machine Learning Engineer who enjoys solving real business problems through machine learning.

The ideal candidate combines strong analytical capabilities with practical software engineering skills and experience deploying ML models into production.

You should be comfortable working with large datasets, collaborating with international teams, and communicating technical insights to business stakeholders.

Experience in recommendation systems, personalization, advertising optimization, or customer behavior modeling would be particularly valuable.

## Description

As a Senior Data Scientist / Machine Learning Engineer, you will develop and deploy advanced machine learning models that directly impact business growth and customer engagement.

You will work on recommendation systems, personalized marketing, customer segmentation, predictive analytics, and advertising optimization.

This is a hands-on position covering the complete machine learning lifecycle, from exploratory data analysis and feature engineering to model deployment, monitoring, and continuous optimization.

You will collaborate with international engineers, data scientists, product teams, and business stakeholders to transform complex business challenges into scalable AI solutions., * Develop and deploy machine learning models for personalized marketing and advertising optimization.

 * Design and implement recommendation engines using machine learning and deep learning techniques.
 * Build predictive models for customer lifetime value (CLV), customer behavior, and engagement.
 * Develop advanced customer segmentation models using clustering and behavioral analytics.
 * Perform exploratory data analysis (EDA), data preprocessing, and feature engineering.
 * Lead end-to-end machine learning development, including training, validation, deployment, and monitoring.
 * Design and improve ML pipelines and production-level machine learning systems.
 * Define business KPIs and translate analytical insights into actionable recommendations.
 * Conduct A/B testing, statistical analysis, and model performance evaluations.
 * Collaborate with engineering teams to integrate ML models into production environments.
 * Research and evaluate emerging technologies, including Generative AI, LLMs, NLP, and deep learning.
 * Mentor junior team members and contribute to engineering standards and documentation.