Senior Data and Applied Scientist - Xbox

Microsoft•Redmond, WA

15h

About The Position

Have you or someone you know ever wanted to work in gaming? How about building safe and inclusive communities? How about impacting experience for millions of customers? What if you could do all three of those things at the same time? Microsoft is committed to ensuring that we develop and deploy our AI technologies in ways that uphold our AI principles and warrant people’s trust. Here in Microsoft Gaming, we are on a mission to bring the joy and community of gaming to everyone on the planet. We deliver on that vision by putting players at the center, enabling you to play the games you want, with the people you want, anywhere you want. Gaming Player Services and Operations is at the heart of our ambition to reach billions of players across the globe, ensuring that every player feels included and engaged across Xbox. We do this through our commitment to driving operational excellence through innovation and ensuring player and partner delight across Microsoft Gaming. As a Senior Data and Applied Scientist, you will work with cross-functional teams to apply state-of-the-art AI that supports community moderation experiences for some of the largest online communities around the globe. You will also collaborate with other teams across Xbox, Microsoft, and the gaming industry to ensure the developed technology complies with legal and regulatory requirements, as well as best practices for online safety, privacy and responsible AI. You will be a peer mentor and role model on the team, fostering a culture of customer focus, collaboration, diversity, inclusion, and drive technical excellence and innovation. Within the Safety, Trust, & Responsibility team, our mission is to grow and protect global player communities. We believe that wherever you play, it should be a fun, safe, and inclusive environment—and it’s our job to provide the services, expertise, and support to make accessible, world-class player experiences possible. We champion transparency, compliance, and the responsible use of AI, with trust at the core of how we operate. We embrace experimentation to reach more players, inform business decisions, and deepen our understanding of customer and player needs. Through a culture of innovation, collaboration, and continuous improvement, we support and challenge one another to perform at our best.

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) 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 3+ 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 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience.

Nice To Haves

Several years of industry experience across multiple AI modalities, such as multimodal models, Automatic Speech Recognition (ASR), Computer Vision, and Natural Language Processing (NLP).
Hands-on experience with advanced fine-tuning methods, including self-supervised, semi-supervised, and supervised learning techniques.
Hands-on experience building or evaluating large language models and small language models, (LLM/SLM) applications in production, ensuring AI meets or exceeds targets for functionality, responsiveness and compliance.
Product-driven thinking.
Experience designing and implementing processes/systems to measure and improve AI product performance throughout the product life cycle.
Ability to work in a fast-paced environment, manage multiple priorities, and adapt to changing requirements and deadlines
Experience building large data sets using SQL, Spark, Snowflake etc., for model training, testing and/or deriving actionable insights.
Strong communication skills to explain insights in an understandable way to non-experts, in both formal presentations and informal group conversations.
Committed to contributing to an inclusive workplace that focuses on respect, integrity, and personal accountability.

Responsibilities

Advancing the state-of-the-art artificial intelligence (AI) and natural language processing (NLP) algorithms, especially applying large language models and small language models, (LLM/SLM) to real-world large-scale content moderation systems.
Developing tools, algorithms, fine-tuning and optimizing AI models, and automated systems that help identify and moderate high-risk behaviors and user generated text, image, video, audio and mixed media content on social networks
Working on the full lifecycle of AI development including training data collection, feature engineering, model training, offline and online experimentation, and deployment and maintenance.
Collaborating and working cross functionally, focusing on strategic business questions, and sharing learnings.
Driving product and business innovations for measurable impact on moderation product effectiveness.
Investigating new technologies, tools, and prototypes, the latest techniques to evolve AI capabilities of the product and organization.

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