データサイエンティスト/データアナリスト、残業なし（原則定時退社）、400万円以上の転職・求人情報

求める人材: Roles & Responsibilities * Own the overall program delivery, ensuring alignment to business goals, contractual commitments, and delivery milestones * Define and govern the program delivery model, including workstream structure, governance cadence, and decision-making mechanisms * Coordinate delivery across multiple pods and teams including TPM, FDE, Technical Lead, and engineering teams * Establish and maintain program-level plans, milestones, dependencies, and critical path visibility * Oversee end-to-end execution across application development, AI implementation, data workflows, and platform delivery * Ensure technical and business workstreams remain aligned, removing blockers and resolving delivery conflicts proactively * Own program-level risk management, dependency management, and issue escalation frameworks * Drive executive-level governance including status reporting, decision support, and escalation management * Oversee release planning, deployment coordination, and production readiness across delivery streams * Ensure technical delivery aligns with architectural principles, scalability requirements, and operational readiness expectations * Partner with TPMs to ensure sprint-level execution aligns with broader program milestones * Partner with FDEs and Technical Leads to ensure solution implementation quality and technical delivery predictability * Monitor delivery performance using structured delivery metrics, milestone health, and quality indicators * Drive recovery planning and delivery rebaselining when execution risks emerge * Manage vendor coordination and third-party delivery dependencies where applicable * Ensure compliance, governance, and audit requirements are embedded into program execution * Drive continuous improvement in delivery practices, governance models, and operational efficiency Skills & Requirements Experience * 8+ years of experience in delivery management, program management, or large-scale technical delivery leadership * Proven experience managing complex multi-stream technology programs * Experience leading cross-functional teams across business, engineering, data, and platform workstreams * Experience owning enterprise-scale delivery outcomes with accountability for timelines, quality, and execution predictability Program & Delivery Management * Strong expertise in program planning, milestone management, and integrated delivery oversight * Strong experience managing cross-team dependencies, sequencing, and delivery coordination * Strong experience in risk identification, mitigation planning, and issue escalation management * Strong experience in delivery recovery planning and rebaselining * Experience in vendor coordination and partner delivery management Technical Delivery Understanding * Strong understanding of software delivery lifecycle (SDLC) and Agile delivery models * Strong understanding of application development, system integration, and cloud-native delivery models * Strong understanding of AI/ML-enabled application delivery, including LLM workflows, RAG implementations, and evaluation cycles * Working understanding of technical architecture, APIs, microservices, and data integration patterns * Ability to engage credibly with Technical Leads, architects, and engineering teams on technical dependencies and delivery risks Governance & Delivery Metrics * Strong experience establishing program governance structures and reporting frameworks * Experience defining and monitoring delivery KPIs, milestone health, risk dashboards, and quality metrics * Strong escalation governance and decision management capability * Strong experience maintaining delivery transparency through structured reporting and stakeholder communication Financial & Commercial Management * Experience in budget management, cost tracking, and delivery financial governance * Experience managing delivery efficiency and resource optimization * Ability to manage commercial implications of delivery changes, scope shifts, and recovery plans Compliance & Operational Governance * Familiarity with compliance, governance, and audit requirements (e.g., GDPR, SOC2, ISO) * Experience embedding governance controls into delivery execution * Understanding of release governance, change control, and production readiness practices Ways of Working * Strong experience with Agile, Scrum, SAFe, and hybrid delivery methodologies * Ability to coordinate sprint-level execution into program-level outcomes * Strong stakeholder alignment capability across business and technical teams Soft Skills * Strong leadership and program ownership mindset * Strong executive communication and stakeholder management capability * Strong decision-making capability under ambiguity and delivery pressure * Strong escalation management and structured problem resolution * Strong cross-functional collaboration and conflict resolution capability * Strong ability to balance business priorities with technical realities * High accountability for delivery outcomes and program stability Nice to Have * Experience leading AI, data, or cloud transformation programs * Experience in enterprise modernization or digital transformation programs * Experience in telecommunications or regulated enterprise environments * Experience managing globally distributed or multicultural teams * Experience managing multi-vendor delivery ecosystems * Japanese language proficiency preferred for Japan-based or customer-facing programs

求める人材: Roles & Responsibilities * Engage directly with customers to understand business challenges, technical requirements, and operational constraints * Translate customer requirements into solution designs, technical workflows, and implementation plans * Design, develop, and deploy production-grade applications using Python, JavaScript, or related technologies * Build and integrate LLM-powered applications, including conversational systems, automation workflows, and knowledge-based systems * Design and implement Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, embedding strategies, retrieval optimization, and response orchestration * Build and manage agent-based architectures, including task orchestration, tool integration, and execution flows * Design and maintain evaluation frameworks to measure model quality, retrieval effectiveness, and output reliability * Implement and manage MLOps/LLMOps pipelines covering deployment, monitoring, versioning, rollback, and lifecycle management * Develop and deploy applications in cloud environments such as AWS, Azure, or GCP * Collaborate with data engineers, architects, and technical leads to integrate AI workflows into enterprise systems * Identify technical risks and implementation bottlenecks, proposing mitigation strategies proactively * Balance rapid prototyping with production-readiness, ensuring quality, scalability, and maintainability * Support optimization of delivery workflows by leveraging AI tools to improve engineering productivity and operational efficiency Skills & Requirements Experience * Minimum 5 years of experience in software engineering, technical implementation, or related technical delivery roles * Proven experience driving projects with direct client engagement and stakeholder management * Experience working in fast-paced, ambiguous delivery environments with strong ownership and execution capability Application Engineering * Strong hands-on development experience using Python and/or JavaScript * Experience building production-grade backend services, APIs, and application workflows * Strong understanding of software engineering fundamentals including modular design, testing, and maintainability * Experience integrating frontend and backend components for end-to-end solution delivery Applied AI Engineering * Demonstrated experience building or implementing applications leveraging Large Language Models (LLMs) and Generative AI technologies * Practical experience designing and implementing Retrieval-Augmented Generation (RAG) workflows * Experience in agent design, orchestration logic, and tool-based execution patterns * Experience building evaluation frameworks for model validation, retrieval quality, and output consistency * Understanding of prompt engineering, model behavior optimization, and AI system reliability Cloud & Platform Engineering * Experience building and deploying systems in cloud environments (AWS, GCP, Azure) * Experience with containerized deployment and cloud-native architecture patterns * Understanding of deployment automation, CI/CD pipelines, and infrastructure provisioning * Familiarity with application scalability, resilience, and cloud cost optimization MLOps / LLMOps * Experience designing and operating MLOps and/or LLMOps pipelines * Understanding of model lifecycle management including deployment, versioning, monitoring, and rollback * Experience implementing observability for AI systems, including performance and quality monitoring Customer Delivery & Stakeholder Engagement * Strong ability to engage with customers to clarify requirements, align expectations, and drive delivery decisions * Ability to explain complex technical concepts to business and non-technical stakeholders * Experience balancing customer priorities with technical feasibility and delivery constraints Soft Skills * Strong problem-solving orientation with a customer-first mindset * Ability to balance hands-on coding with customer-facing engagement * Strong decision-making capability under ambiguity * Ability to maintain delivery speed without compromising quality * Strong ownership and accountability for delivery outcomes * Ability to remain composed and effective in high-pressure delivery environments Nice to Have * Experience implementing large-scale enterprise systems * Experience in data security, governance, and access control design * Experience working in startup or new business environments * Experience collaborating with global or distributed teams * Strong English communication skills * Experience with observability tools and operational monitoring for AI systems

求める人材: Roles & Responsibilities * Design and implement complex application features across frontend, backend, and AI workflow layers * Independently develop and maintain backend services and APIs using Python and FastAPI * Build frontend interfaces and interaction layers using React, Next.js/Remix, and Tailwind CSS * Implement real-time streaming workflows using Server-Sent Events (SSE) or similar technologies * Design and implement LLM-integrated applications, including business workflow automation and knowledge retrieval systems * Build and optimize Retrieval-Augmented Generation (RAG) pipelines, including advanced retrieval strategies, hybrid search, and re-ranking techniques * Develop and maintain evaluation loops to measure AI output quality, retrieval effectiveness, and guardrail compliance * Design and implement guardrails and control mechanisms to improve safety, reliability, and output consistency * Contribute to architecture decisions related to service decomposition, integration patterns, and scalability * Build and optimize data pipelines, data transformation workflows, and data quality validation mechanisms * Implement and optimize CI/CD pipelines, deployment automation, and infrastructure provisioning workflows * Ensure systems meet security requirements, including authentication, authorization, and access control enforcement * Implement observability standards including logging, monitoring, tracing, and alerting * Review code, mentor junior engineers, and enforce engineering quality standards * Translate business and product requirements into technical specifications and implementation plans * Troubleshoot complex issues across application, AI, and infrastructure layers Skills & Requirements Experience * 4 to 6 years of software development experience * Experience building production-grade software systems, including exposure to AI-enabled or data-driven systems * Proven ability to independently own features and contribute to architectural decisions Architecture & System Design * Strong understanding of microservices architecture patterns and service decomposition * Experience implementing Test Driven Development (TDD) and structured testing practices * Strong understanding of database design principles across SQL and NoSQL systems * Ability to design scalable, maintainable, and resilient application components Frontend Development * Strong experience in React development * Experience building responsive interfaces using Tailwind CSS * Familiarity with Next.js or Remix frameworks * Understanding of SSE (Server-Sent Events) for real-time communication and streaming interactions Backend Development * Strong hands-on experience with Python development * Strong expertise in FastAPI and modern API development practices * Strong understanding of REST API principles, service integration, and backend architecture * Experience building scalable backend workflows and asynchronous processing patterns AI / ML Engineering * Strong understanding of LLM integration patterns and AI application workflows * Hands-on experience implementing advanced RAG architectures * Experience with Hybrid Search and Re-ranking strategies for retrieval optimization * Experience designing and maintaining evaluation loops for model quality and response consistency * Experience implementing Guardrails for safe and reliable AI behavior Data Engineering * Experience in data exploration and profiling * Experience building and maintaining data pipelines * Understanding of data quality validation and data integrity practices * Familiarity with structured and semi-structured data handling patterns DevOps & Cloud Engineering * Strong working knowledge of Docker and Kubernetes * Experience implementing and maintaining CI/CD pipelines * Hands-on experience with Infrastructure-as-Code (Terraform) * Understanding of cloud-native deployment patterns and release management Security & Observability * Strong understanding of IAM, OAuth2, and secure API design * Familiarity with network policies and service security controls * Experience implementing monitoring and observability using Prometheus, Grafana, and OpenTelemetry Engineering Practices * Strong debugging and troubleshooting capability across application and AI layers * Strong understanding of testing strategies and engineering quality practices * Experience in collaborative development and version control workflows * Ability to document technical decisions, designs, and implementation patterns clearly Soft Skills * Strong ownership and accountability for delivery outcomes * Ability to communicate technical trade-offs and architecture decisions clearly * Strong collaboration and adaptability in cross-functional teams * Leadership capability in guiding junior engineers and supporting team delivery * Strong problem-solving mindset with structured scenario analysis * Ability to translate business requirements into technical implementation plans * Reliability mindset with focus on system stability and maintainability * Openness to feedback and continuous improvement Nice to Have * Experience with LLM orchestration frameworks such as LangChain or similar * Exposure to vector databases and semantic search systems * Experience working with cloud platforms (AWS, Azure, GCP) * Experience in AI-first product or platform engineering environments * Experience supporting enterprise-scale AI implementations * Trial period 3 months; salary and conditions unchanged during trial Working hours Fixed-hours system, 9:00–18:00, 60-min break, 8 working hours Holidays and leave Two full days off per week (Sat/Sun), public holidays, year-end/New Year, summer leave, 10 days annual paid leave after 6 months, condolence/celebration leave, maternity/childcare/nursing-care leave (with take-up record); [n] days off per year Salary Annual ¥6,000,000–¥12,000,000 paid in 12 instalments); set on experience and skills; no fixed overtime included, overtime paid separately in full Raise and bonus Raise once a year (April); bonus twice a year (June and December), subject to company results and individual evaluation Social insurance Full coverage: health insurance, employees' pension, employment insurance, workers' accident insurance; enrolled from date of hire in accordance with law Benefits Annual health check, certification support (exam and renewal fees), book allowance, external training and conference fees, company PC and monitor, GPU/cloud environment provided, casual dress Passive smoking Indoor smoking prohibited Reason for hiring Additional headcount to strengthen the AI product development team Selection process Document screening → first interview (online) → technical assignment or technical interview → final interview → offer; as fast as 2 weeks from application