Role intent Live

Senior Applied Scientist

Microsoft

Work Mode

Onsite

Employment Type

FULL TIME

Location

India, Karnataka, Bangalore

Application Deadline

September 21, 2026

Design, train, evaluate, and improve ML models and signals that power search and personalized discovery experiences. Mentor and guide colleagues without formal research backgrounds on ML best practices, experimentation, and evaluation.

Responsibilities

Solve complex relevance and ranking problems using applied machine learning and statistical methods. Integrate scientific methods into the product lifecycle, including offline evaluation, metric design, and online experimentation. Write productionquality code and apply strong debugging, validation, and reliability practices in largescale ML systems. Collaborate closely with software engineers, product managers, designers, and partner science teams to drive endtoend impact from research to production. Share learnings and results through design reviews, internal presentations, and external publications or patents where appropriate.

Required Qualifications

Bachelor'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 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 4+ year(s) related experience (e.g., statistics, predictive analytics, research). OR equivalent experience. 6+ years of experience in predictive analytics, statistical modelling, or applied ML, including data preparation and evaluation. Experience with synthetic data generation and data management for evaluation/training. Proficiency in English with solid cross functional collaboration and communication skills. Experience working with largescale, production ML systems in search, ranking, or recommendation domains. Exposure to large language models (LLMs) or generative AI techniques applied in practical product scenarios. Experience publishing peer reviewed papers or patents.

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