Senior Applied Scientist

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In Feeds and AI team, we’re building Microsoft Start, a content powerhouse for every person on the planet to be informed, entertained, and inspired. Microsoft Start is the place for all to read, watch, listen, create, connect with people of shared interests, and experience wonders in the world.

We are looking for a skilled and experienced Senior Applied Scientist to join our ranking foundation team. As a Senior Applied Scientist focusing on recommender systems, you will play an important role in contributing to the development and optimization of our online services and offline pipelines within our content ecosystem to achieve product and business growth goals.

Required qualifications:
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.

• Minimum of 3 years of professional experience in recommender systems, search engines, or online advertising, with strong expertise in machine learning algorithms, generative AI and large language models (LLMs), statistics, and data mining techniques applied to personalization.
• Proven problem-solving abilities and a track record of thriving in fast-paced, collaborative environments. Excellent communication and teamwork skills, with the ability to clearly articulate complex technical concepts to a variety of audiences.
• Proficient in Python programming, with additional experience in languages such as C# or C++ considered a plus.

Additional or preferred qualifications:
Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.

• 3+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
• Experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
• 3+ years experience conducting research as part of a research program (in academic or industry settings).
• 1+ year(s) experience developing and deploying live production systems, as part of a product team.
• 1+ year(s) experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.

• Drives product impact by transferring cutting-edge research into production systems. Collaborates across Microsoft and external groups to apply scalable, data-driven solutions, author white papers, file patents, and consult on product strategy.
• Designs and optimizes ranking algorithms across L1–L3 stages using collaborative filtering, deep neural networks (DNN), and graph neural networks (GNN). Applies FastRank and LambdaMart techniques for precision ranking in Bing Feeds and other verticals.
• Leads experimentation and deployment of large-scale NLP and LLM models for topic modeling, sentiment analysis, and multimodal content linking. Supports real-time indexing and modular APIs for rapid model onboarding.
• Cleans, transforms, and analyzes large-scale data to build usable datasets and optimize feature selection. Develops ETL pipelines and mentors teams in data preparation and signal system design.
• Operates on distributed GPU/CPU frameworks (DLTS, DeepSpeed) for training and inference. Supports A/B testing, flighting, and real-time feedback loops to refine models and improve user engagement.
• Applies deep understanding of fairness and bias in model development. Contributes to internal ethics policies and ensures representative data usage aligned with responsible AI principles.
• Coaches junior team members, collaborates with academia to recruit top talent, and shares research findings through publications and conferences. Builds multidisciplinary teams and fosters innovation culture.