

th ofshare by the state-of-the-art online advertising platform and servicebidding, Large Language Model and Large
As aApplied Scientist inMicrosoft Ads team, you willfocus on.in certain algorithm.for youto workfrom home partially.
Bringing the State of the Art to Products
new technologyand approaches into production by applying long-term research efforts to solve immediate product needs.
With limited guidance from others,approach, and applies, improves, or creates a research-backed solution (e.g., novel, data driven, scalable, extendable) to positively
Capability Management and Networking
Maintains ties with external network of peers andprospective talent, when asked. May contribute to publications on research findings. Mayawareness of their work.
Reinforces a positive environment by applying best practices. May support mentorship by
Performs documentation of work in progress, experimentation results, plans, etc. Documents scientific work to ensure process is captured. Participates in the creation of informal documentation and may share findings to promote innovation within
Leveraging Applied Research
research. Asks probing questions to better understand strategy.
Gains deep knowledge in a service, platform, or domain andproduct domain by reviewing products.
Machine Learning Functionality, Insights, and Technical Tools
Prepares data to be used for analysis by reviewing criteria that reflect quality and technical constraints. Reviews data and suggests data to be included and excluded. Describes actions taken to address data quality problems.with the development of
Uses machine learning algorithms that structures, analyzes, and uses data in product and platforms to train algorithms for scalable artificial intelligence solutions before deploying.
data toassumptions about the data while also reviewing consistency against other sources. Begins to independently run basic descriptive, diagnostic, predictive, and prescriptive statistics.
Supports the application and use of intelligence created during the training of algorithms for deployment. Seeks information about large-scale computing frameworks, data analysis systems, and modeling environments to improve models.
Leverages or designs and uses machine learning/data extraction, transformation, and loading (ETL) of pipelines (e.g., data collection, cleaning) based on data prepared.
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