Tech Bilingual Data Scientist Global AI CompanyMachine Learning Engineer | Up to 14M | Tokyo Hybrid

The company develops AI-powered customer engagement and marketing automation platforms that help enterprise businesses optimize customer communication improve engagement and drive revenue growth.

With approximately 6.3 billion in total funding rapid business expansion and an international workforce representing around 20 nationalities the company offers an exciting opportunity to work on large-scale AI products in a global environment.

The organization develops its own AI and data capabilities leveraging proprietary first-party data and customer-provided zero-party data to build advanced machine learning solutions.

• Salary: annually
  
• Location: Tokyo (Aoyama)
  
• Work Style: Hybrid approximately 4 days remote per week (1 office day recommended)
  
• Working Hours: Flextime (Core Hours: 10:0016:00)
  
• Japanese: Business Level Required
  
• English: Ability and willingness to communicate in technical discussions
  
• Employment: Permanent / Full-Time
  

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.
  

• 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.
  

• Experience building recommendation systems ranking algorithms or personalization engines.
  
• Knowledge of collaborative filtering matrix factorization neural collaborative filtering or Two-Tower models.
  
• Experience with MLOps model monitoring retraining pipelines and online inference.
  
• Experience with AWS GCP or Azure particularly AWS.
  
• Experience with Snowflake Redshift PostgreSQL or other data platforms.
  
• Knowledge of Apache Airflow AWS Step Functions Apache Spark or Kafka.
  
• Experience developing scalable ML APIs using FastAPI or Flask.
  
• Experience with high-throughput low-latency machine learning services.
  
• Experience with deep learning NLP LLMs or Generative AI.
  
• Experience in advertising technology recommendation systems search ranking or marketing analytics.
  
• Contributions to open-source projects research publications or Kaggle competitions.
  

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.

• Hybrid working environment with flexible working arrangements.
  
• International engineering team with members from approximately 20 nationalities.
  
• Flextime system with core hours from 10:00 to 16:00.
  
• Opportunities to develop production-level AI and machine learning systems.
  
• Access to large-scale proprietary datasets.
  
• Professional development support including up to 55000 annually for books and seminars.
  
• Social insurance and transportation allowance.
  
• Paid annual leave summer holidays and year-end holidays.
  
• Health and wellness support programs.
  
• Opportunities for career advancement into ML Tech Lead Principal Data Scientist or AI/ML Engineering Management roles.