Snr Applied Scientist

Job description

**Overview** Microsoft Clarity is building the next generation of intelligent web analytics and user understanding experiences. Our Clarity Science team leverages large-scale behavioral data, machine learning, deep learning, and large language models to help businesses better understand customer journeys, optimize conversions, personalize user experiences, and unlock actionable insights. As an Snr Applied Scientist, you will work on some of the most challenging and impactful problems in the web intelligence space, including conversion understanding, user profiling, identity resolution across devices and sessions, 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 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. 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** - 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. **Qualifications** **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. - Atleast 7 years industry experience as an Applied Scientist. - Data-centric and analytical mindset with a solid focus on experimentation and measurable impact. - Good problem-solving skills and good understanding of algorithms and data structures. - Fluency with at least one programming language such as Python, C#, Java, or Scala. - Hands-on experience in large language models (LLMs), pretrained language models (PLMs), machine learning (ML), and deep learning (DL). **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. - Ability to learn quickly, work independently in complex situations, and deal with ambiguity. - Experience with big data platforms and distributed processing technologies. - Hands-on experience in NLP, information retrieval, ranking, or recommendation systems. - Understanding of data analytics and visualization tools. - Experience working with customer behavior data, user journeys, digital analytics, or advertising systems. - Good communication and collaboration skills with the ability to influence cross-functional stakeholders. #MicrosoftAI This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. --- Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about [**requesting accommodations.**](https://careers.microsoft.com/v2/global/en/accessibility.html)