Principal Metrics Data Scientist Information Technology (IT) - Redmond, WA at Geebo

Principal Metrics Data Scientist

Microsoft s mission is to empower every person and every organization on the planet to achieve more.
As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals.
Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.
The Core Search and Artificial Intelligence (AI) team is the leading applied machine learning team at Microsoft responsible for delivering the quality experience to over 100M daily active users around the world in Microsoft s search engine, Bing.
Beyond Bing other search engines such as Yahoo, DuckDuckGo, and new startups like You.
com depend on us as well.
We are looking for a Principal Metrics Data Scientist join the Core Search team.
This team is extremely data driven and without good metrics we can t make a good product.
Come help us make quality metrics so there can be a globally competitive market for online search.
Required
Qualifications:
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5
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 7
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 10
years data-science experience (e.
g.
, managing structured and unstructured data, applying statistical techniques and reporting results)OR equivalent experience.
Preferred
Qualifications:
Experience with human in the loop machine learning.
Experience with real world system building and data collection, including design, coding and evaluation Experiment using Large Language Models (LLMs) to build reliable offline metrics.
Customer focused, strategic, drives for results, is self-motivated, and has a propensity for action Problem solver:
ability to solve problems that the world has not solved before Data Science IC5 - The typical base pay range for this role across the U.
S.
is USD $133,600 - $256,800 per year.
There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $173,200 - $282,200 per year.
Certain roles may be eligible for benefits and other compensation.
Find additional benefits and pay information here:
Microsoft is an equal opportunity employer.
All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.
We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
#WWE# #CoreSearch#Measurement:
Define, invent, and deliver metrics which accurately measure the quality of online information, and the satisfaction/success of our customers.
Models:
Develop Machine Learning (ML)/Statistical models to measure/predict the quality of online content and/or user interactions with large scale AI systems.
Experimental Design:
Think critically about sampling and experimental design.
Developing innovative strategies and products in these areas.
Crowdsourcing:
Apply behavioral insights, game theory, and social scientific understanding to measure and improve the performance of a global workforce employed to label online content.
Strategy:
Translate strategy into plans that are clear and measurable, with progress shared out monthly to stakeholders Cooperation:
Partner with program management, engineers, and other areas of the business Employment typeFull-TimeWork siteUp to 100% work from homeRole typeIndividual ContributorDisciplineData ScienceProfessionResearch, Applied, & Data Sciences.
Estimated Salary: $20 to $28 per hour based on qualifications.

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