Principal Applied Scientist (Shopping)

Overview

Microsoft Shopping is building the next generation of intelligent web analytics and user understanding experiences. Our team leverages large-scale behavioral data, machine learning, deep learning, and large language models to help users find the product they are looking for at the best deal.

As a Principal Applied Scientist, you will work on some of the most challenging and impactful problems in the web intelligence space, including conversion understanding, user profiling, shopping and commerce intelligence, and AI-powered customer journey insights. You will partner closely with engineers, product managers, and data scientists to transform massive datasets into intelligent products that serve millions of users and businesses worldwide.

This role is ideal for candidates who enjoy solving ambiguous problems, working with petabyte-scale data, applying modern AI techniques, and driving innovations from research concepts to production deployment.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Responsibilities

• Discover and apply insights from massive data sets of structured, semi-structured, and unstructured data.
• Identify opportunities to leverage available data to resolve customer pain points.
• Own data science projects end to end starting from problem definition, data exploration/preparation, model building, and model evaluation.
• Develop and deploy machine learning, deep learning, and LLM-based solutions for conversion understanding, user profiling, identity linking, and commerce intelligence scenarios.
• Prototype and rapidly evaluate creative ideas to gain insights into their strengths and weaknesses.
• Partner with engineering and product teams to translate scientific innovations into scalable production systems.
• Storytelling and visualization capabilities to deliver the right message to the concerned audience.
• Design metrics that serve as the North Stars for team efforts and A/B testing framework to support data-driven decisions.
• Drive experimentation and data-driven decision making through rigorous offline and online evaluation methodologies.
• Stay current with emerging trends in AI, machine learning, NLP, recommender systems, and user behavior modeling.

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 4+ 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.
• Demonstrated understanding of machine learning and deep learning algorithms.
• Demonstrated foundation and hands on experience with AI, agents, including context engineering, fine tuning, RAGs, agentic engineering
• Data-centric & Analytical Mindset.
• Problem-solving skills.
• Ability to learn quickly, work independently in complex situations, and deal with ambiguity.
• Fluency with scripting/programming language: Python

Preferred Qualifications

• Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.
• Experience with large data modeling, handling specially for customer facing applications.
• Understanding of big data tools: Spark
• Understanding of cloud platforms: Azure, AWS, or Google.
• Understanding of data analytics/visualization tools such as PowerBi, Tableau
• Understanding of database systems: SQL and NoSQL.
• Understanding of ML frameworks: TensorFlow, Keras, PyTorch, or Caffe

Additional information

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.