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Senior Applied Scientist
China, Jiangsu, Suzhou; China, Beijing, Beijing; China, Shanghai, Shanghai
·
On-site
·
Full-time
·
2mo ago
Required Skills
Python
R
SQL
Machine Learning
Deep Learning
Statistical Analysis
Overview
Microsoft Store is a digital distribution platform developed by Microsoft on Windows Desktop. It serves as a centralized hub for users to discover, download, and manage various types of applications, software, games, and other digital content. The vision of the Microsoft Store aligns with Microsoft’s broader mission to empower individuals and organizations to achieve more through technology. The store aims to provide users with a convenient and secure platform to access a diverse range of high-quality digital content that enhances productivity, creativity, and entertainment on Windows devices.
We are seeking a motivated and strategic-thinking Senior Applied Scientist to join the Microsoft Store China team. In this role, you will have the opportunity to impact millions of store users, enabling them to enjoy a diverse array of benefits and features that elevate their digital experience.
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.
Responsibilities
- Collaborate closely with cross‑functional partners—including product managers, engineers, and designers—to define, refine, and review product requirements and technical specifications.
- Leverage Generative AI to enhance Microsoft Store user engagement by improving Merchandising efficiency and scaling high‑quality content operations.
- Optimize recommendation algorithms and AI‑driven solutions across scenarios such as click‑through rate prediction, conversion rate prediction, and user intent understanding.
- Lead the development, experimentation, and continuous performance optimization of machine learning models in both pre‑production and production environments.
- Maintain and iterate on production AI solutions and models, improving stability, efficiency, and robustness through systematic engineering enhancements.
- Research and evaluate cutting‑edge methodologies in recommendation systems, machine learning, and AI to drive innovation in product experience.
- Design and implement data processing pipelines, including data transformation, feature engineering, and quality validation, to support large‑scale machine learning workflows.
- Adhere to principled data collection practices and policies.
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
OR
- Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year related experience
OR equivalent experience - 4+ years of experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
- 3+ years of industry experience with implementing statistical models, machine/deep learning, and analysis (Recommenders, Prediction, Classification, Clustering, etc.) in big data environment.
Other Requirements:
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:-Microsoft Cloud Background Check: This position will be required to pass the
- Microsoft Cloud background check upon hire/transfer and every two years thereafter. “
Preferred Qualifications:
- Master’s Degree in related field AND 6+ years related experience
OR
- Doctorate in related field AND 3+ years related experience
OR equivalent experience - Experience with experiments, machine learning, anomaly detection, predictive analysis, exploratory data analysis, and/or other areas of data science on a large-scale product.
- Experience with languages like C#/Java.
- Engineering experience using large data systems on SQL, Hadoop, Hive queries, etc.
#W+DJOB
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.
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About Microsoft
Reviews
3.8
5 reviews
Work Life Balance
4.1
Compensation
4.3
Culture
3.4
Career
3.2
Management
3.0
65%
Recommend to a Friend
Pros
Excellent compensation and benefits package
Four-day workweek with improved work-life balance
Supportive managers and teams
Cons
High-pressure environment causing anxiety
Unprofessional interview processes
Limited creative work opportunities
Salary Ranges
5,571 data points
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Mid/L4 · Data and Applied Scientist
0 reports
$202,099
total / year
Base
$149,342
Stock
$32,252
Bonus
$20,505
$139,572
$301,212
Interview Experience
7 interviews
Difficulty
3.7
/ 5
Duration
14-28 weeks
Offer Rate
14%
Experience
Positive 14%
Neutral 29%
Negative 57%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Technical Interview
5
Onsite/Virtual Interviews
6
Final Round
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
News & Buzz
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·
5w ago