> Markdown version of [/jobs/ext/2589557-principal-staff-data-scientist](https://www.wearedevelopers.com/jobs/ext/2589557-principal-staff-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal / Staff Data Scientist - **Company:** Xsolla (USA), Inc. - **Location:** United States (Remote available) - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Artificial Neural Networks, Code Generation, Cursor (Graphical User Interface Elements), Fraud Prevention and Detection, Video Game Development, Machine Learning, Systems Integration, Supervised Learning, Large Language Models, Deep Learning, Xgboost, Machine Learning Operations - **Published:** August 2, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=767106796b42f44e ## About the Role Modeling Depth * Advanced Degree in Statistics, machine learning or related areas. Experience in statistics/ML expertise with a track record of leading high-impact data science initiatives at scale of billions of transactions. * Hands-on experience creating, training and fine-tuning models not just integrating hosted model APIs. You should be able to walk through the data, the objective, what broke, and the before/after evaluation numbers, and why the model did not perform as expected. * Experience owning models in production: deployment, monitoring, drift detection, retraining - with real latency budgets, not just research notebooks. * Production experience with classical ML for fraud/anomaly detection, recommendation, or churn/LTV (gradient boosting, deep learning, graph-based models). Technology Familiarity * Supervised learning, transfer leaning on machine learning as well as neural networks * Basic LLM knowledge, especially how to use it and where not to use it. * MLOps foundations: feature stores, experiment tracking, model registries (MLflow/W&B-class), continuous training pipelines. * Model serving and inference optimization (vLLM-class serving, quantization)., * Publications, conference talks, or recognized open-source contributions to training/eval tooling . * Graph-based fraud detection (fraud rings, device/account linkage).. * Gaming, payments, fraud, advertising domain experience. * Hands-on, up-to-date experience with modern AI tools (e.g., Claude, Copilot, Cursor) for code generation, review, and accelerating day-to-day engineering work. ## Description If you are ambitious, energized by solving challenging technical problems, passionate about developing talent, and excited to influence the future of ML/AI in the video game industry, this could be the perfect role for you. ## Related Videos - [Leapter: The Reinvention of Software Development? A Future Built On AI Generated Code.](https://www.wearedevelopers.com/videos/1663-leapter-the-reinvention-of-software-development-a-future-built-on-ai-generated-code) - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [TikTok's Privacy Innovation](https://www.wearedevelopers.com/videos/1036-tiktok-s-privacy-innovation) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Building a Friendly Kotlin SDK to Connect to JetBrains Space](https://www.wearedevelopers.com/videos/128-building-a-friendly-kotlin-sdk-to-connect-to-jetbrains-space) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)