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Scopely

Creates and runs games with ongoing updates

AI Data Specialist

Data EngineeringConfirmed live in the last 24 hours
Full-timeTokyo, JapanNo salary listed

About the Job

Requirements

  • At least 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 such as BigQuery or Snowflake; data transformation and modeling such as dbt; business intelligence and semantic layers such as Looker; and workflow orchestration such as 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 the 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 large language model applications, AI agents, Model Context Protocol or similar tool-integration layers, retrieval-augmented generation, 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; experience 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, CRM, or Game Operations teams; 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 the Tokyo office three days per week.

Responsibilities

  • Partner cross-functionally with stakeholders across Product, LiveOps, Marketing, User Acquisition, 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 large language models, agents, retrieval-augmented generation 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, User Acquisition 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 the 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 continuous integration.

Desired Qualifications

  • Enjoy helping teams become more capable by building practical systems that combine better tools, trusted data, and thoughtful automation to support faster, better-informed decisions.
  • Passion for games and player behavior; experience with free-to-play mobile, live-service, or location-based products; and familiarity 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.

About the Company

Scopely

Creates and runs games with ongoing updates

Scopely develops, publishes and operates video games for players on mobile devices, computers and consoles. Its portfolio includes MONOPOLY GO!, made in partnership with Hasbro, and location-based games such as Pokémon GO, whose teams joined its Scopely Explore business. Game teams add events, social features and content updates so players can keep returning to the same game over time. Many titles are free to start and earn money through optional in-game purchases, supported by the proprietary Playgami platform and shared publishing services across owned and partner studios. Scopely was founded in 2011 and is headquartered in Culver City, California.

Company size
1,001-5,000
Company stage
Acquired
Total funding
$998.8M
Headquarters
Culver City, CA
Founded
2011

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