AI & Advanced Analytics - Data & Engineering Roles | Tokyo

Join a high-impact AI & Advanced Analytics consulting practice in Tokyo, where you will help organisations design, develop and deploy enterprise-grade artificial intelligence solutions, scalable data platforms and production-ready software systems.

This opportunity welcomes experienced professionals across four specialist disciplines: AI / Technical Architecture, Data Engineering, Data Science and Software Engineering. Depending on your expertise and seniority, you will contribute to different stages of the AI development lifecycle, from strategic solution design to production deployment and ongoing optimisation.

You will work in multidisciplinary consulting teams alongside industry specialists, product managers, software engineers, data professionals and senior business stakeholders. Together, you will translate complex commercial challenges into practical technology solutions that deliver measurable business value.

For professionals specialising in AI Architecture, the role offers opportunities to define enterprise-wide technical strategies, evaluate cloud infrastructure and design secure, scalable architectures that connect advanced analytics with existing business systems.

Data Engineers will focus on building reliable data foundations, including modern data pipelines, ETL/ELT workflows, distributed processing environments and cloud-based data platforms that support advanced analytics and machine learning applications.

Data Scientists will apply statistical modelling, predictive analytics, machine learning, deep learning and generative AI to solve complex business problems, ensuring that model performance and explainability align with commercial objectives.

Software Engineers will develop and deploy the production applications that bring AI solutions to life, using modern APIs, microservices, containerisation, CI/CD pipelines and MLOps practices to deliver reliable enterprise software.

Across all disciplines, the practice emphasises technical excellence, collaborative problem-solving and responsible AI development. You will be expected to balance innovation with practical considerations such as security, maintainability, operational performance and business impact.

This is an excellent opportunity for an experienced AI Architect, Data Architect, Data Engineer, Data Scientist, Machine Learning Engineer, Software Engineer or MLOps specialist looking to work on complex, high-value transformation programmes within a consulting environment.

Key Responsibilities

• Collaborate with cross-functional consulting teams, domain specialists, product managers and executive stakeholders to design and deliver enterprise AI and advanced analytics solutions.
• Translate complex business requirements into scalable technical architectures, data platforms, machine learning models and production software applications.
• For AI / Technical Architecture roles, define end-to-end solution architectures covering technology selection, data integration, infrastructure and deployment.
• Evaluate AWS, Microsoft Azure, Google Cloud Platform (GCP), hybrid cloud environments and enterprise integration requirements, balancing performance, cost, security and maintainability.
• For Data Engineering roles, design and optimise ETL/ELT pipelines, batch and streaming data workflows, feature stores and modern cloud data platforms.
• Modernise legacy data systems and implement data lakes, lakehouses and data warehouses, maintaining high standards of data governance, security and quality.
• For Data Science roles, develop and validate predictive models, statistical solutions, machine learning algorithms, deep learning applications, NLP and generative AI systems.
• Apply rigorous model evaluation practices, including experimental design, explainability, fairness assessments and business-aligned performance metrics.
• For Software Engineering roles, develop and maintain APIs, microservices and user-facing applications powered by advanced analytics and AI.
• Implement CI/CD pipelines, containerised deployment, automated testing and MLOps processes to support reliable production operations and model retraining.
• Promote strong engineering practices, including clean code, code reviews, version control, test-driven development (TDD) and comprehensive technical documentation.
• Communicate technical recommendations and project outcomes to business leaders, enterprise architects and non-technical stakeholders, ensuring alignment between engineering decisions and business objectives.

Required Skills and Qualifications

Experience:

• Relevant professional experience in at least one of the following disciplines: AI / Technical Architecture, Data Engineering, Data Science or Software Engineering.
• For AI / Technical Architects: Strong experience in enterprise software architecture, cloud platforms such as AWS, Azure or GCP, microservices, security compliance and hybrid cloud integration.
• For Data Engineers: Advanced proficiency in SQL and Python or Scala, with experience in distributed data processing technologies such as Apache Spark, Ray or Dask.
• For Data Engineers: Experience with workflow orchestration tools such as Apache Airflow, Prefect or Dagster, and modern data platforms or tools including dbt, Snowflake or Databricks.
• For Data Scientists: Advanced proficiency in Python or R, with practical experience using machine learning libraries such as scikit-learn, PyTorch, TensorFlow or XGBoost.
• For Data Scientists: Strong understanding of statistical modelling, machine learning techniques and experimental design.
• For Software Engineers: Experience developing applications using languages such as Python, Go, Java or TypeScript, including REST or gRPC API development.
• For Software Engineers: Experience with Docker, Kubernetes, Infrastructure as Code tools such as Terraform, and production MLOps frameworks.
• A Bachelor's, Master's or PhD degree in Computer Science, Data Science, Engineering, Mathematics, Statistics or an equivalent quantitative discipline.
• Demonstrated experience working in cross-functional agile teams, including exposure to code reviews and test-driven development practices.

Soft Skills:

• Strong ability to translate complex technical concepts into clear, actionable business insights for non-technical stakeholders.
• Excellent analytical thinking, structured problem-solving and technical decision-making abilities.
• Collaborative approach to working with consultants, engineers, product managers, domain specialists and executive stakeholders.
• Practical, delivery-focused mindset with an understanding of how technical choices influence business outcomes.
• Ability to evaluate trade-offs involving scalability, cost, security, maintainability and operational performance.
• Commitment to engineering excellence, continuous learning and effective teamwork within agile delivery environments.

Language Requirements:

• Japanese: Native-level proficiency, supporting effective communication with Japanese business stakeholders and client teams.
• English: Fluent proficiency, enabling collaboration with international colleagues and communication of complex technical concepts.

Preferred Skills & Qualifications

• Experience delivering enterprise AI, advanced analytics or digital transformation projects within a management consulting or professional services environment.
• Exposure to generative AI, large language models (LLMs), natural language processing (NLP) or advanced machine learning applications.
• Experience designing or operating large-scale cloud-native data and AI platforms across AWS, Azure or GCP.
• Familiarity with production MLOps, model monitoring, automated retraining and continuous deployment practices.
• Experience communicating technical strategy or solution architecture to senior business leaders, enterprise architects and executive stakeholders.
• Understanding of responsible AI, algorithmic fairness, model explainability, data governance and enterprise security requirements.

About the Company

Our client is seeking experienced technology professionals to join a high-impact AI & Advanced Analytics consulting practice focused on solving complex enterprise business challenges.

The practice brings together specialists across Data Science, Data Engineering, Software Engineering and Technical Architecture, combining complementary technical expertise to deliver integrated solutions.

Its approach is built around multidisciplinary collaboration, bringing technology professionals together with industry specialists, product managers and senior stakeholders to address business problems from both technical and strategic perspectives.

The organisation focuses on designing and deploying enterprise-grade AI products, scalable data platforms and production-ready analytics applications that create practical value for clients.

A defining principle of the practice is Hybrid Intelligence at Scale - テクノロジーと人間の洞察の融合. This approach combines advanced machine learning technologies with deep industry expertise and informed human judgement to support meaningful business transformation.

By joining the team, you will contribute to high-stakes AI and advanced analytics initiatives, helping organisations modernise their technology capabilities and apply intelligent solutions to important business challenges.

Why You'll Love Working Here

• Join a high-impact AI & Advanced Analytics consulting practice working on complex enterprise challenges.
• Choose a career path aligned with your expertise in AI Architecture, Data Engineering, Data Science or Software Engineering.
• Contribute to the development of enterprise-grade AI products and scalable data platforms.
• Work with generative AI, machine learning, modern cloud technologies and advanced analytics engineering practices.
• Collaborate with multidisciplinary teams combining technical specialists, industry experts and product professionals.
• Engage with senior business stakeholders and enterprise technology leaders on strategically important initiatives.
• Develop experience across the end-to-end AI lifecycle, from architecture and data engineering to modelling and production deployment.
• Apply responsible AI principles, robust engineering standards and measurable business performance metrics.
• Strengthen your professional expertise through exposure to complex technical challenges and cross-functional consulting engagements.
• Help organisations realise the potential of Hybrid Intelligence at Scale, combining cutting-edge technology with human insight to transform business operations.

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