Microsoft · 3 days ago
Principal Data Scientist, Minecraft
Redmond, WA
Full-time
Onsite
Senior Level, Lead/Staff
$140K/yr - $275K/yr
5+ years expMicrosoft is the creator of Minecraft and is on a mission to build a better world through the power of play. The Principal Personalization Data Scientist will lead the technical strategy and execution of AI-driven personalization products to enhance player engagement and connection with content.
Agentic AIApplication Performance ManagementArtificial Intelligence (AI)Business DevelopmentDevOpsInformation ServicesInformation TechnologyManagement Information SystemsNetwork SecuritySoftware
Responsibilities
Design and implement large-scale Search and Personalization systems—including real-time recommendations, ranking, and re-ranking—that are simple, extensible, maintainable, and well-documented
Lead design, implementation, and code reviews across Search and Personalization services (candidate generation, ranking, re-ranking, real-time features) to ensure consistency, performance, reliability, and technical excellence
Scale personalization and search systems to support a massive global player base and a rapidly growing content catalogue, ensuring high availability, low latency, and predictable performance under heavy load
Continuously improve existing pipelines (data ingestion, feature engineering, model training/inference, indexing, retrieval) to reduce latency, increase relevance, and elevate overall player experience
Maintain robust automated testing and evaluation frameworks, including unit/functional tests, offline relevance metrics, and online A/B experiments with clear guardrails, success criteria, and regression monitoring
Drive player-centric quality and usability by instrumenting telemetry, monitoring model and search behavior in production (drift, bias, safety, query performance), and iterating based on player outcomes and feedback
Act as DRI (Designated Response Individual) /ICM (Directly Responsible Individual) during incidents and high-urgency events, ensuring timely triage, root-cause identification, communication with stakeholders, and stabilization of Search and Personalization systems
Qualification
Required
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience
Preferred
Experience in AI/ML (Artificial Intelligence/Machine Learning) principles, frameworks, and tools (e.g., Generative AI, RAG (Retrieval-Augmented Generation) with experience in big-data technologies like Spark (PySpark) and Databricks
Expertise in recommender systems and search algorithms and architectures: collaborative filtering, matrix factorization, graph-based methods, deep-learning rankers, contextual bandits, reinforcement-learning approaches, indexing, retrieval, relevance modeling, ranking, and hybrid search (vector + keyword)
Software-engineering fundamentals and ability to write production-quality code using modern development practices (GitHub, CI/CD, code reviews)
Understanding of representation learning: user/item embeddings, sequence models, transformer-based architectures, and two-tower models
Expertise in evaluation methods: offline metrics (NDCG, MAP, recall@K, coverage, diversity), validation strategies, and designing/analyzing online experiments (A/B tests, guardrails, statistical significance)
Skilled in MLOps (Machine Learning Operations) practices: CI/CD for ML, feature stores, model-training pipelines, deployment workflows, and monitoring for latency, drift, bias, and performance
Expertise in real-time serving architectures: low-latency APIs, distributed serving systems, caching strategies, vector databases, and scalable cloud infrastructure
Experience designing, deploying, and monitoring large-scale ML and personalization systems in production
Familiarity with multiple ML domains: NLP (Natural Language Processing), predictive modeling, time-series forecasting, deep learning, and reinforcement learning
Games-industry knowledge
Verbal and written communication skills; ability to translate complex technical concepts to non-technical stakeholders
Company
Microsoft
Microsoft is a software corporation that develops, manufactures, licenses, supports, and sells a range of software products and services.
10001+ employees
H1B Sponsorship
Microsoft has a track record of offering H1B sponsorships. Please note that this does not
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reference. (Data Powered by US Department of Labor)
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2025 (9192)
2024 (9343)
2023 (7677)
2022 (11403)
2021 (7210)
2020 (7852)
Funding
Current Stage
Public CompanyTotal Funding
$1MKey Investors
Technology Venture Investors
2022-12-09Post Ipo Equity
1986-03-13IPO
1981-09-01Series Unknown· $1M
Leadership Team
Satya Nadella
Chairman and CEO
Vukani Mngxati
Chief Executive Officer - Microsft South Africa
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