招聘
Overview
The IDEAS Security Data Science team focuses on building AI‑ and agent‑centric data science solutions that power Microsoft Security products and experiences. We partner closely with Security engineering and product teams to translate complex, high‑signal data into intelligent systems, automated decisioning, and measurable business and product impact. Our work spans AI agents, applied machine learning, security telemetry, experimentation, and executive‑ready insights that drive growth, protection, and operational excellence across the Security portfolio.
As a Senior Data Scientist in Security Data Science, you will lead the development of AI‑first and agent‑driven analytical solutions by default. You will design and productionize models, agents, and data products that directly influence security product experiences, customer outcomes, and business decisions. This role requires strong applied ML skills, comfort working with LLM‑based systems, deep analytical rigor, and the ability to mentor others while operating in close partnership with engineering and product.
This position is based at the Redmond campus with 3 days per week work in the office and 2 days per week work from home. Relocation assistance is available.
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 Agent & AI‑Centric Solution Development (Primary Responsibility)
o Design, build, and iterate on AI‑ and agent‑based solutions that operate by default in Security product workflows.
o Develop intelligent systems using ML, LLMs, and retrieval‑augmented approaches to automate analysis, decisioning, and insight generation.
o Partner with engineering and PM to productionize agents and AI features with real customer and business impact.
o Define success metrics and telemetry for AI agents and continuously improve them using feedback loops.
Statistical Analysis & Experimentation
o Design and execute controlled experiments to validate product and business hypotheses.
o Apply advanced statistical techniques (e.g., regression, causal inference, Bayesian methods) to security and product data.
o Clearly communicate uncertainty, limitations, and confidence to stakeholders.
Model Development & Deployment
o Develop predictive and prescriptive models using machine learning and AI techniques.
o Ensure models and agents are production‑ready, scalable, and aligned with privacy, security, and compliance requirements.
o Monitor performance post‑deployment and iterate using telemetry and user feedback.
Business & Product Impact
o Translate complex analytical and AI‑driven outputs into clear product and business recommendations.
o Influence Security product strategy and prioritization through data and experimentation.
o Collaborate cross‑functionally to align analytics, agents, and AI investments with organizational goals.
Data Engineering & Infrastructure
o Build ad‑hoc and production‑grade data pipelines over large‑scale security and product telemetry.
o Partner with Data Engineering teams to ensure secure, reliable, and scalable data infrastructure.
o Implement best practices for data quality, governance, and observability.
Leadership & Mentorship
o Coach and mentor junior data scientists on applied ML, experimentation, and AI‑first development.
o Drive adoption of agent‑centric and AI‑native patterns across the team.
o Contribute to standards for experimentation, metrics, and responsible AI usage.
Qualifications Required Qualifications:
- 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 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 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 equivalent experience.
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:
- Programming: Python, SQL (R optional)
- Machine Learning & AI: supervised/unsupervised learning, model evaluation, applied ML systems
- Statistics: experimentation, hypothesis testing, causal inference
- Data Engineering: Spark, data pipelines, Azure Data Lake
- Experience working with production data systems and distributed architectures.
- Ability to explain complex technical topics to non‑technical audiences.
- Experience building AI‑ or agent‑based systems, including LLM‑enabled workflows.
- Familiarity with ML/AI deployment pipelines and observability.
- Background working with security, trust, privacy, or compliance‑sensitive data.
- Ability to influence decisions through clear, concise storytelling with data and metrics.
#DPG #DPGHiring
Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $158,400 - $258,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
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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关于Microsoft

Microsoft
PublicMicrosoft Corporation is an American multinational technology conglomerate headquartered in Redmond, Washington.
10,001+
员工数
Redmond
总部位置
$3000B
企业估值
评价
3.8
5条评价
工作生活平衡
4.1
薪酬
4.3
企业文化
3.4
职业发展
3.2
管理层
3.0
65%
推荐给朋友
优点
Excellent compensation and benefits package
Four-day workweek with improved work-life balance
Supportive managers and teams
缺点
High-pressure environment causing anxiety
Unprofessional interview processes
Limited creative work opportunities
薪资范围
5,620个数据点
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Mid/L4 · Applied Science
1份报告
$234,166
年薪总额
基本工资
$180,128
股票
-
奖金
-
$234,166
$234,166
面试经验
1次面试
难度
4.0
/ 5
时长
14-28周
体验
正面 0%
中性 0%
负面 100%
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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