Senior Applied Scientist Job at Microsoft Corporation (Redmond)

Senior Applied Scientist

Microsoft Corporation

Location:
United States , Redmond

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

119800.00 - 234700.00 USD / Year

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Job Description:

Are you ready to make a global impact that has visible impact on consumers? Join Bing Multimedia AIGC (AI Generated Content) team at Microsoft, where we experiment, learn and deliver rich creation experiences to consumers worldwide. As part of Microsoft AI, our team is taking a giant step in advancing and incorporating AI into our search experience, delivering new and exciting AI creation features withe state-of-the-art models. There is no limit to creativity in our work, at a scale and reach that is unmatched. As a Senior Applied Scientist in Bing Multimedia AIGC team, you will help us to build and improve AIGC experiences on Bing, that are extensible and usable on other Windows products, including Copilot. You will research and develop an understanding of metrics, tools, data workflows, hill-climbing methods used to measure AIGC's success metric, and deep analysis of our product quality to inform strategic business directions. Together with our business owners, you will be challenged with defining the best business measurement methodology to prove a working business model for how Search and Creations integrate as one product. You will also have the opportunity to fine-tune optimizations for our creation models.

Job Responsibility:

Leverages data analysis knowledge to clean, transform, analyze, integrate, and organize data to the level required by the analysis techniques selected
Develops useable datasets for modeling purposes
Scales the feature ideation and data preparation
Takes cleaned or raw data and adapts data that for machine learning purposes
Uses understanding of which features are important that come out of the model and identifies the optimal features
Identifies gaps in current datasets and drives onboarding of new datasets
Works with team to optimize signal system design
Identifies gaps in current datasets and drives onboarding of new datasets (e.g., bringing on third-party datasets)
Leverages or designs and uses machine learning/data extraction, transformation, and loading (ETL) pipelines (e.g., data collection, cleaning) based on data prepared and guides team to do so
Influences the direction of the team
Establishes the pipeline so that the team can conduct all of their experiments and data processing
Uses data pipelines for training, as well as for shipping models which should execute correctly
Establishes collaborative relationships with relevant product and business groups inside or outside of Microsoft and provides expertise or technology to create business impact
Takes initiative and drives activities such as technology transfers attempts, standards organizations, filing patents, authoring white papers, developing or maintaining tools/services for internal Microsoft use, or consulting for product or business groups
May publish research to promote receiving new intellectual property for business impact
Independently works to create product impact
Identifies approach, and applies, improves, or creates a research-backed solution (e.g., novel, data driven, scalable, extendable) to positively impact a Microsoft product
Designs an approach to solve significant business problems shared by a senior team member
May publish research to promote receiving new intellectual property for product impact
Performs documentation of work in progress, experimentation results, plans, etc
Documents scientific work to ensure process is captured
Creates informal documentation and may share findings to promote innovation within group or with other groups
Uses deep understanding of fairness and bias
May contribute to ethics and privacy policies related to research processes and/or data/information collection by providing updates and suggestions around internal best practices
Seeks to identify potential bias in the development of products
Helps address scalability problems by adjusting to stakeholder needs
Works with large-scale computing frameworks, data analysis systems, and modeling environments to improve models
Applies the model to real products, and then verifies effects through iterations
Experiments by putting multiple models in production and evaluating their performance
Continues to monitor how algorithm performs against expected behaviors and performance or accuracy guardrails
Monitors over time for input and output data that there are changes over time
Uses system to run analyses on an ongoing basis such as by comparing predicted value with actual value
Collaborates with others and helps lead others to leverage data to identify pockets of opportunity to create state-of-the-art algorithms to improve a solution to a business problem
Consistently leverages knowledge of techniques to optimal analysis using algorithms
Identifies opportunity areas regarding new statistical analyses and drives solutions
Uses statistical analysis tools or modifies existing tools for evaluating Machine Learning models and validates assumptions about the data while also reviewing consistency against other sources
Runs basic descriptive, diagnostic, predictive, and prescriptive statistics
Represents the team's insights
Characterizes the customer's problem through metrics to measure the quality of machine learning systems
Calibrates metrics to support decision making for data (e.g., gaining awareness of ideal metrics and use of metrics).

Requirements:

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience.

Nice to have:

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience
OR equivalent experience
1+ year(s) experience developing and deploying live production systems, as part of a product team
1+ year(s) experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.

Additional Information:

Job Posted:
May 05, 2026

Employment Type:

Fulltime

Work Type:

On-site work

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