AI Data Specialist - Tokyo

Scopely Explore is seeking a highly motivated AI Data Specialist/ Engineer to join our Tokyo Studio, supporting Monster Hunter Now and Pikmin Bloom. This role will sit at the intersection of data engineering, AI tooling, marketing, live game operations, and product strategy.

Responsibilities

Partner cross-functionally with stakeholders across Product, LiveOps, Marketing, User Acquisition (UA), CRM, and Game Operations to identify and prioritize high-impact data and automation opportunities and translate ambiguous business needs into reliable AI-native technical systems; Build and operate scalable data models, pipelines, semantic layers, and self-service data products using BigQuery, dbt, Looker, Airflow, and related cloud technologies; Develop production-quality AI-enabled workflows using technologies such as LLMs, agents, retrieval-augmented generation (RAG) knowledge systems, evaluation frameworks, and human-in-the-loop review patterns to help teams investigate performance, detect anomalies, prepare decision briefs, and plan and evaluate campaigns; Partner with Marketing to improve and automate workflows for audience segmentation, campaign performance, UA governance and execution, reactivation, event planning, and post-launch analysis; Safeguard data quality and metric consistency across game, marketing, and executive reporting while promoting responsible AI use through appropriate evaluation, oversight, and human review; Create reusable internal tools, patterns, and documentation that make AI accessible to non-technical teams while preserving trust, reviewability, and clear source-of-truth data; Contribute hands-on to Tokyo Studio’s broader AI operating model and help teams adopt effective AI-enabled workflows; Use AI-assisted engineering tools responsibly by validating generated code and analysis through rigorous review, automated testing, and established quality gates (including linting, type checking, and CI) before production

Requirements

5+ years of experience in data engineering, analytics engineering, machine learning engineering, or a closely related role; Deep expertise designing, building, deploying, and operating production data platforms across cloud data warehousing (e.g., BigQuery or Snowflake), data transformation and modeling (e.g., dbt), business intelligence and semantic layers (e.g., Looker), and workflow orchestration (e.g., Airflow), with demonstrated ownership of reliability, observability, data quality, performance, cost efficiency, and production troubleshooting; Exceptional SQL skills and strong data-modeling fundamentals, including dimensional modeling, metric design, semantic layers, and scalable analytical data products, along with strong ability to write clean, maintainable production code for pipelines, automation, integrations, and AI-enabled workflows; Hands-on experience building AI solutions for real business workflows, including LLM applications, AI agents, Model Context Protocol (MCP) or similar tool-integration layers, retrieval-augmented generation (RAG), prompt and tool orchestration, and model evaluation; Strong judgment and hands-on experience establishing data-quality controls, consistent metric definitions, and responsible AI practices across data and AI-enabled systems (including reliability, privacy, access control, explainability, evaluation, and human review) and validating AI-generated code and analysis through code review and automated testing; Experience building tools for and working directly with Product, LiveOps, Marketing, User Acquisition (UA), CRM, or Game Operations teams, with the ability to identify and prioritize high-impact opportunities and translate ambiguous business and operational needs into durable technical systems that teams can trust and reuse; Experience building reusable internal data and AI tools and driving adoption among technical and non-technical users through documentation, training, and hands-on enablement, while contributing to AI operating models through shared standards, governance, ownership, and review practices across functions and regions; Excellent business-level verbal and written communication in both English and Japanese; Ability to work from Scopely Explore’s Tokyo office three days per week

Nice to have

Enjoy helping teams become more capable by building practical systems that combine better tools, trusted data, and thoughtful automation; Passionate about games and player behavior; Experience with free-to-play mobile, live-service, or location-based products; Familiar with real-world or social mobile games such as Monster Hunter Now, Pikmin Bloom, or Pokémon GO; Experience modernizing prototype or locally operated data workflows into reliable, scalable, cloud-managed production systems