Description
Summary
Microsoft AI are looking for a talented Senior Applied Scientist at their Redmond office. This role sits at the heart of strategic decision-making, transforming complex data into high-quality and rich actionable insights for Microsoft Advertising stakeholders. You'll work directly with leadership to shape the company's direction in the AI and machine learning markets.
About the Role
As a Senior Applied Scientist, you will lead the development of machine learning solutions leveraging SOTA technologies in GenAI to build predictive models for generating recommendations, detecting anomalies, generating automated insights with reasoning, and ensuring the platform delivers accurate, actionable intelligence at scale. You will drive experimentation and validation of models, mentor junior scientists, and contribute to model governance and Responsible AI practices.
Accountabilities
- Lead the design and implementation of machine learning models for recommendations, anomaly detection, and actionable insights.
- Drive experimentation and validation of models.
- Mentor junior scientists and contribute to model governance and Responsible AI practices.
- Partner with engineering and BI teams to operationalize insights into dashboards and alerting systems.
The Candidate we're looking for
Experience:
- 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.
Technical skills:
- 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.
Personal attributes:
- Strong communication and collaboration skills.
- Ability to work in a fast-paced environment and adapt to changing priorities.
Benefits
- Competitive salary.
- Comprehensive benefits package.
- Opportunities for professional growth and development.
- Collaborative and dynamic work environment.