Senior Applied Scientist(MSAI)

Collaborates with appropriate stakeholders to determine user requirements for a scenario. Drives identification of dependencies and the development of design documents for a product, application, service, or platform. Creates, implements, optimizes, debugs, refactors, and reuses code to establish and improve performance and maintainability, effectiveness, and return on investment (ROI).

Leverages subject-matter expertise of product features and partners with appropriate stakeholders (e.g., project managers) to drive a workgroup's project plans, release plans, and work items. Proactively seeks new knowledge and adapts to new trends, technical solutions, and patterns that will improve the availability, reliability, efficiency, observability, and performance of products while also driving consistency in monitoring and operations at scale.

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. 5+ years hands-on experience in C#, Python, C+ + or other programming languages.

English reading and writing skills and fluent English speaker. Experience in search, information retrieval, data mining or NLP related area. Experience in LLM application.

Ability to derive creative and innovative solutions by thinking "outside the box". Experience and passion in designing, developing and shipping high quality software products, systems and services Ability to collaborate and drive results in a cross-group/team project. AI native mindset and experience: demonstrated ability to leverage AI/ML (e.g., LLMs, agents, copilots, automation tools) to improve personal and team productivity, accelerate experimentation, or unlock new product ideas.