As a Senior Applied Scientist at Microsoft Copilot, you will lead the development of machine learning and generative AI systems that enhance product discovery, ranking, and personalization in conversational shopping experiences. This role combines applied machine learning, generative AI, and product experience, with a focus on creating trustworthy user-facing Copilot features. You will work closely with product, engineering, and design teams to ensure the successful implementation of these models. The position emphasizes innovation, collaboration, and a commitment to responsible AI practices.

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience.
• Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience.
• Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience.
• 3+ years of hands-on experience developing machine learning or statistical models.
• Proficiency in programming for data science using Python or R and experience with SQL.

• Design, build, and productionize machine learning models for product discovery, ranking, recommendation, and personalization.
• Develop LLM-based systems for conversational shopping, including prompt design and tool orchestration.
• Address quality and trust challenges such as hallucination risk and recommendation reliability.
• Define evaluation frameworks and experimentation strategies for conversational shopping scenarios.
• Partner closely with product, engineering, and design teams to translate models into reliable Copilot experiences.
• Provide technical leadership for applied science within Copilot Shopping through design reviews and mentoring.
• Contribute to model governance and Responsible AI practices to ensure trustworthy systems.

• Employees at Microsoft are often offered comprehensive, “world-class” benefits—including health and mental-wellness programs, competitive pay with bonuses and stock awards, and retirement/savings options. Time-off and flexibility are common, with generous vacation and holidays, parental and caregiver leave, and flexible work schedules, alongside learning support, employee resource groups, product discounts, and matching-gifts/volunteering programs. Specific benefits can vary by region.