LEAD MACHINE LEARNING /ANALYTICS ENGINEER - MONOPOLY GO!

Scopely is looking for a Lead ML/Analytics Engineer to join our Monopoly Go! team in Barcelona on a hybrid basis.
At Scopely, we care deeply about what we do and want to inspire play, every day - whether in our work environments alongside our talented colleagues, or through our deep connections with our communities of players.
We are a global team of game lovers who are developing, publishing and innovating the mobile games industry, connecting millions of people around the world daily.
Monopoly GO! is our new casual game and a key franchise that has just become one of Scopely's largest games enjoyed by millions of players.
The team is based in Europe and the US, and works every day to create captivating new experiences for our players.
What You'll Do You'll join a cross-functional team focused on building scalable, production-ready machine learning systems that power key business decisions.
Your work will sit at the intersection of data science, analytics engineering, and infrastructure, turning prototypes into systems that operate reliably at scale.
You'll help bridge the gap between experimentation and production, enabling rapid iteration and strong engineering standards.
Develop, maintain, and scale ML pipelines for use cases such as churn prediction, recommendation systems, and personalization Own the deployment lifecycle of machine learning models, from automated training and testing through CI/CD to monitoring and alerting in production Collaborate with Data Scientists and Analytics Engineers to transform research prototypes into robust, reproducible code ready for deployment Build and manage cloud-native infrastructure, leveraging GCP services like BigQuery, Cloud Composer (Airflow), Dataproc, and Cloud Run Drive high engineering standards - writing clean, modular, and tested code in Python and contributing to shared libraries and tools Design and optimize data pipelines using dbt and BigQuery, enabling high-quality datasets for analytics and ML Contribute to the infrastructure stack for ML and data pipelines using Docker, Kubernetes, and (ideally) Terraform Actively contribute to planning discussions, proactively propose improvements, and take ownership of deliverables You take initiative, solve problems autonomously, and are comfortable operating with minimal guidance What We're Looking For Solid track record of deploying and maintaining ML systems in production environments Strong Python skills and comfort working as a software engineer - well-structured, maintainable code is a must Experience with machine learning libraries like scikit-learn, TensorFlow, or PyTorch Hands-on experience with CI/CD for ML (e.
.
automated retraining, testing, and deployment) Deep familiarity with cloud infrastructure, ideally GCP, and modern DevOps practices Proficiency in SQL and experience designing data models and transformations using dbt Experience orchestrating workflows with Airflow or Cloud Composer Solid understanding of ML concepts (training, validation, evaluation), along with an ability to translate business problems into data-driven solutions Experience with version control tools like Git and collaborative workflows (e.
., pull requests, code reviews) Comfortable working with experimentation techniques (e.
.
A/B testing, hypothesis testing) to evaluate model and product impact Excellent communication skills and a collaborative mindset - able to work across functions and explain complex topics to non-technical stakeholders A high valuation of business context and the drive to achieve technical excellence An inclination towards collaboration and pride in contributing to high-functioning teams Enjoyment in working within fast-paced, growth-oriented environments Bonus points Experience with real-time model serving, online/offline feature pipelines, or recommendation systems.
Prior exposure to the gaming industry, player behavior modeling, or dynamic content personalization.
Experience with infrastructure-as-code tools like Terraform.
Passion for mentoring and supporting the growth of less experienced team members.
Solid understanding of data modeling principles (e.
., Kimball methodology, star schemas).
Passion for AI (LLM) Engineering.
At Scopely, we create games for everyone - and want to ensure that the people behind our games reflect that! We are committed to creating a diverse, supportive work environment where everyone is treated with respect.
We are committed to providing equal employment opportunities and welcome individuals from all backgrounds to join us & embrace the adventure! About Us Scopely is a global interactive entertainment and mobile-first video game company, home to many top, award-winning experiences such as "MONOPOLY GO!," "Star Trek™ Fleet Command," "Stumble Guys," "MARVEL Strike Force," and "Yahtzee® With Buddies," among others.
Scopely creates, publishes, and live-operates immersive games that empower a directed-by-consumer™ experience across multiple platforms--from mobile, web, PC and beyond.
Founded in , Scopely is fueled by a world-class team and a proprietary technology platform Playgami that supports one of the most diversified portfolios in the games industry.
Recognized multiple times as one of Fast Company's "World's Most Innovative Companies," Scopely is a multi-billion-dollar business due to its ability to create long-lasting game experiences that players enjoy for years.
Scopely has global operations in more than a dozen markets across Asia, EMEA, and North America, and is home to many internal game development teams, referred to as Scopely Studios, with additional game studio partners across four continents.
Scopely was acquired by Savvy Games Group in July for $4.
billion, and is now an independent subsidiary of Savvy.
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