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Microsoft AI (MAI) builds an integrated consumer AI ecosystem across search, browsing, and content, focused on delivering trustworthy, scalable experiences with durable user and business value. The MAI Ecosystem Data Science Team owns MAI wide metrics, shared measurement systems, and experimentation frameworks to enable consistent, high confidence decisions and optimize MAI level outcomes. We are seeking a Principal, Data Science & Analytics for ecosystem data science to own cross product measurement strategy, partner across product and business teams, and uphold a high bar for metric quality, statistical rigor, and data driven leadership. We are looking for high-energy Data Scientist, creative modeling geeks who are willing to work in a dynamic environment to solve real life day to day problems, leveraging data science techniques. You will enjoy and be successful in this role if you are curious and willing to challenge the status quo and come up with data driven solutions to ambiguous problems.
Job Responsibility:
Leadership: Mentor data scientists and align work with MAI ecosystem goals, driving technical excellence, innovation, and cross-team collaboration
Data Strategy & Execution: Develop ecosystem data strategies for marketplace and system performance, including standardized data collection, analysis, reporting, and interpretation
validate analytical approaches and results
Advanced Analytics & Measurement: Apply machine learning, statistical modeling, data mining, and experimentation to large datasets
define and deliver metrics that accurately measure user and business value across products and marketplace components
Experimental Design & Implementation: Design and execute experiments across user and demand dimensions
translate strategy into clear, actionable, and measurable plans, sharing progress and results with stakeholders
Collaboration: Partner closely with product, program management, engineering, and business teams to integrate data science solutions into shared platforms and marketplace operations
Performance Optimization: Identify cross-team opportunities for product and process improvement
implement data-driven solutions to improve efficiency, reliability, and user experience
Influence & Decision-Making: Engage stakeholders with clear, compelling, and actionable insights
make independent decisions for the team and handle complex tradeoffs to drive product and service improvements
Technical & Operational Leadership: Develop and standardize processes for data acquisition, quality, and operationalizing ML models
provide expert review of analysis and modeling
lead adoption of new tools and technologies to improve availability, reliability, efficiency, and performance
Standards & Trusted Advisory: Establish and uphold standards, policies, and best practices for high-quality, efficient, and extensible code
influence business, customer, and solution strategy with a solid customer focus
act as a trusted advisor across the ecosystem
Requirements:
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data science experience
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience
OR equivalent experience
Nice to have:
6+ years of experience in at least one of programming languages like Python/R/MATLAB/C#/Java/C++
Great organizational, analytical, data science skills and intuition
Fantastic problem solver: ability to solve problems that the world has not solved before
Interpersonal skills: cross-group and cross-culture collaboration
Experience with real world system building and data collection, including design, coding and evaluation
Excellent communication to be able to communicate insights to senior leaders
Experience with driving large collaboration across multiple teams
Experience with communicating with different audiences to provide insights
Demonstrated experience in applying statistics, experimentation and metrics to generate clear actionable insights