Bilingual Data Scientist

Job Description

Senior Data Scientist (Bilingual)

Location: Tokyo/Osaka

Employment Type: Full-time, Permanent

Annual Salary: ¥8,000,000-¥14,000,000

Working Style: Hybrid, approximately one recommended office day per week

Position Overview

We are looking for an experienced Data Scientist / Machine Learning Engineer to lead the development and production deployment of machine learning solutions for customer personalization, recommendation systems, advertising optimization, and predictive analytics.

This position combines hands-on technical development with business-facing collaboration. You will own the end-to-end machine learning lifecycle, from data exploration and feature engineering through model deployment, monitoring, and continuous improvement.

You will also work closely with business stakeholders to define KPIs, translate business challenges into actionable analytical solutions, and deliver measurable improvements in customer engagement and business performance.

Key Responsibilities

• Develop machine learning models for personalized messaging, advertising optimization, customer lifetime value prediction, and customer segmentation.
• Design, implement, and improve recommendation systems using machine learning and deep learning techniques.
• Conduct exploratory data analysis, data preprocessing, feature engineering, and data validation.
• Define business KPIs and communicate data-driven recommendations to technical and non-technical stakeholders.
• Evaluate model performance using cross-validation, A/B testing, statistical analysis, and error analysis.
• Deploy, monitor, maintain, and continuously improve production machine learning systems.
• Build and maintain feature pipelines, model retraining workflows, and MLOps processes.
• Apply emerging AI technologies, including deep learning, NLP, LLMs, and generative AI, where appropriate.
• Maintain production-quality code, technical documentation, version control, and development standards.
• Mentor junior team members and contribute to engineering best practices.

Required Qualifications

• 4+ years of professional experience in data science, machine learning, or a related field.
• Strong knowledge of machine learning algorithms, statistical modeling, and experimentation.
• Hands-on experience with Python, SQL, NumPy, scikit-learn, and PyTorch.
• Experience with prediction, classification, regression, clustering, and model evaluation.
• Experience with the end-to-end ML lifecycle, including deployment and production maintenance.
• Familiarity with Linux, Git/GitHub, Docker, and CI/CD practices.
• Experience integrating ML models into production systems.
• Business-level Japanese proficiency.
• Ability and willingness to participate in technical discussions in English.

Preferred Qualifications

• Experience building recommendation systems, ranking models, personalization solutions, or advertising optimization systems.
• Knowledge of collaborative filtering, matrix factorization, NCF, or Two-Tower architectures.
• Experience with MLOps, online inference, model monitoring, and automated retraining.
• Experience with FastAPI, Flask, or microservices architecture.
• Experience with AWS, Azure, or GCP.
• Familiarity with Snowflake, Redshift, MySQL, or PostgreSQL.
• Experience with Airflow, AWS Step Functions, Kafka, or AWS Kinesis.
• Experience with Hadoop, Spark, or distributed machine learning.
• Experience developing high-throughput, low-latency ML APIs.
• Exposure to LLM fine-tuning, deep learning research, or open-source ML projects.

Ideal Candidate Profile

• Strong analytical and problem-solving skills with a business-oriented mindset.
• Able to explain complex technical concepts to non-technical stakeholders.
• Comfortable collaborating across functions and working in an international environment.
• Proactive in driving projects from discovery to production.
• Interested in mentoring colleagues and improving engineering standards.
• Motivated to apply emerging AI technologies to real-world business problems.

Compensation And Benefits

• Annual salary: ¥8,000,000-¥14,000,000, depending on experience and skills.
• Fixed overtime allowance covering 45 hours per month; additional overtime is paid separately.
• Flexible working hours, with core hours from 10:00-16:00.
• Hybrid working arrangement.
• Annual book and seminar allowance of ¥55,000.
• Commuting allowance, social insurance, health checkups, parental support, and additional company benefits.
• Standard weekends and public holidays, plus annual leave and seasonal holidays.
• Three-month probation period, generally without changes to employment conditions.

The successful candidate will have the opportunity to own production ML solutions, influence business outcomes, and progress toward technical leadership, ML architecture, or management roles.