OverviewConversational commerce introduces challenges that differ from traditional web shopping. Preferences emerge through dialogue, expectations for accuracy and trust are high, and systems must reason over context and frequently changing commerce data.
Microsoft Copilot is building shopping experiences that are conversational, proactive, and trustworthy. As a Senior Applied Scientist, you will lead the development of machine learning and generative AI systems that power product discovery, ranking, personalization, and reasoning across Copilot shopping surfaces. This role sits at the intersection of applied machine learning, generative AI, and product experience, with clear ownership of core shopping intelligence used directly in user-facing Copilot experiences.
Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.
Responsibilities- Design, build, and productionize machine learning models for product discovery, ranking, recommendation, and personalization using large-scale commerce and behavioral data.
- Develop LLM-based systems for conversational shopping, including prompt design, retrieval-augmented generation, tool orchestration, and grounding against structured commerce data.
- Address quality and trust challenges such as hallucination risk, stale data, and recommendation reliability.
- Define evaluation frameworks and experimentation strategies for conversational and proactive shopping scenarios, including offline metrics and online experiments.
- Partner closely with product, engineering, and design teams to translate models into low-latency, reliable Copilot experiences.
- Provide technical leadership for applied science within Copilot Shopping through design reviews, mentoring, and setting quality standards.
- Contribute to model governance and Responsible AI practices to ensure trustworthy and compliant systems.
QualificationsRequired 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.
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 of hands-on experience developing machine learning or statistical models to solve real-world problems (in industry or academic projects), including building and validating algorithms such as regressions, classifiers, or clustering models.
- Proficiency in programming for data science (e.g. using Python or R for data analysis and modeling) and experience with data querying languages (e.g. SQL).
- Big Data & Distributed Computing: Hands-on experience with large-scale data processing using tools like Apache Spark or Azure Databricks for training and inference workflows.
- Advanced Analytics: Skilled in time-series analysis and anomaly detection techniques (e.g., ARIMA, isolation forests) applied to business contexts for actionable insights.
- LLMs & Domain Adaptation: Practical experience with prompt engineering, fine-tuning GPT-like models, and applying LLMs in domain-heavy areas (healthcare, agriculture, social sciences) while ensuring privacy and Responsible AI compliance.
#MicrosoftAI #copilot #shopping
Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800.00 - $234,700.00 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200.00 - $261,000.00 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
