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트렌딩 기업

트렌딩 기업

채용

채용Microsoft

Senior Applied Scientist

Microsoft

Senior Applied Scientist

Microsoft

China, Beijing, Beijing; China, Jiangsu, Suzhou; Taiwan, Taipei City, Taipei

·

On-site

·

Full-time

·

3w ago

필수 스킬

Machine Learning

Overview:

Microsoft is innovating rapidly in advertising to grow its share of this market by providing the advertising industry with the state-of-the-art online advertising platform and service. Bing Ads algorithm team is at the core of this effort, working on the following research & development: Selection(recall), Relevance, User Response Prediction (Click Prediction and Conversion prediction), Autobidding, Advanced AI technology and Large Scale Machine Learning & Serving System. The team is a world-class R&D team of passionate and talented scientists and engineers who aspire to solve challenging problems and turn innovative ideas into high-quality products and services that can help hundreds of millions of users and advertisers, and directly impact our business.

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.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

  • Responsibilities- Bridge research and production to bring state-of-the-art AI solutions into Bing Ads, translating long-term innovation into scalable product improvements.
  • Drive end-to-end enhancements across data preparation, feature development, solution deployment, and performance monitoring to improve ad relevance and system efficiency.
  • Analyze performance rigorously using offline and online testing methodologies, validating assumptions and identifying optimization opportunities.
  • Deliver robust, scalable solutions by applying advanced AI techniques and production-grade data processes to improve quality, efficiency, and reliability.
  • Create direct impact for users and advertisers by improving ranking, targeting, and auction outcomes, while documenting insights and decisions to accelerate innovation.
  • Increase Bing Ads revenue responsibly through measurable system and solution improvements, adhering to ethics and privacy policies throughout data handling and deployment.
  • Collaborate and communicate effectively across research, engineering, and product teams; contribute to knowledge transfer, innovation initiatives.

Qualifications:

Required Qualifications:

  • 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.
  • Good design and problem-solving skills.
  • Ability to learn new techniques from textbooks or research papers and apply them to the business problem at hand.
  • Experiences on ads or recommendation system recall and ranking is a good addition.

Preferred Qualifications:

  • Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
  • OR equivalent experience.
  • 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

총 조회수

0

총 지원 클릭 수

0

모의 지원자 수

0

스크랩

0

Microsoft 소개

Microsoft

Microsoft

Public

Microsoft Corporation is an American multinational technology conglomerate headquartered in Redmond, Washington.

10,001+

직원 수

Redmond

본사 위치

$3000B

기업 가치

리뷰

3.8

5개 리뷰

워라밸

4.1

보상

4.3

문화

3.4

커리어

3.2

경영진

3.0

65%

친구에게 추천

장점

Excellent compensation and benefits package

Four-day workweek with improved work-life balance

Supportive managers and teams

단점

High-pressure environment causing anxiety

Unprofessional interview processes

Limited creative work opportunities

연봉 정보

5,620개 데이터

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Mid/L4 · Applied Science

1개 리포트

$234,166

총 연봉

기본급

$180,128

주식

-

보너스

-

$234,166

$234,166

면접 경험

1개 면접

난이도

4.0

/ 5

소요 기간

14-28주

경험

긍정 0%

보통 0%

부정 100%

면접 과정

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

자주 나오는 질문

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Culture Fit