Overview
On Site
USD 139,900.00 - 274,800.00 per year
Full Time
Skills
Innovation
Collaboration
Accountability
Leadership
Taxonomy
Roadmaps
Data Quality
Supervision
Training
Evaluation
Fraud
Product Engineering
Reporting
Mathematics
Statistics
Econometrics
Economics
Operations Research
Computer Science
Management
Unstructured Data
Screening
PASS
Cloud Computing
Python
SQL
Apache Spark
Databricks
Snow Flake Schema
Apache Kafka
Active Learning
Stakeholder Management
Communication
Analytics
Machine Learning (ML)
Real-time
ICS
Data Science
SAP BASIS
Microsoft
Immigration
Military
Job Details
Overview
Microsoft is a company where passionate innovators come to collaborate, envision what can be and take their careers further. This is a world of more possibilities, more innovation, more openness, and the sky is the limit thinking in a cloud-enabled world.
We are seeking a Principal Data Science Manager to build and lead a hybrid team at the intersection of data labeling/annotation operations and applied data science. Your team will deliver high-quality labeled datasets, active-learning loops that directly improve fraud detection precision/recall, reduce false positives, and speed time-to-mitigation across Microsoft businesses.
You will be a leader who sets strategy, hires and develops talent, drives cross-org execution, and ships measurable impact.
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
Required Qualifications
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
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
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.
Microsoft is a company where passionate innovators come to collaborate, envision what can be and take their careers further. This is a world of more possibilities, more innovation, more openness, and the sky is the limit thinking in a cloud-enabled world.
We are seeking a Principal Data Science Manager to build and lead a hybrid team at the intersection of data labeling/annotation operations and applied data science. Your team will deliver high-quality labeled datasets, active-learning loops that directly improve fraud detection precision/recall, reduce false positives, and speed time-to-mitigation across Microsoft businesses.
You will be a leader who sets strategy, hires and develops talent, drives cross-org execution, and ships measurable impact.
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
- People leadership & org health: Hire, lead, and develop a blended team of data scientists, label-ops leads, and analytics engineers; foster an inclusive culture and career growth.
- Strategy & roadmap: Define the labeling/annotation strategy, taxonomy stewardship, and quality framework aligned to fraud risk priorities and partner roadmaps.
- Active learning & data quality: Design sampling/uncertainty strategies, gold sets, and label accuracy.
- Programmatic labeling: Introduce fragile supervision, heuristics, and graph-derived signals to pre-label data.
- Detection enablement: Partner with engineering and data scientists to integrate labels into feature stores, model training, rules evaluation, and shadow tests.
- Cross-functional influence: Translate ambiguous fraud patterns into clear label definitions and decision rubrics; align with Product, Engineering, and other stakeholders.
- Executive communication: Report business impact and influence prioritization decisions.
- Embody our culture and values .
Required Qualifications
- Doctorate 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 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical technology)
- 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 technology)
- OR equivalent experience.
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/PhD in a quantitative field.
- Hands-on proficiency with Python and SQL; experience with one or more: Spark/Databricks, Snowflake/BigQuery, Airflow, Kafka/PubSub, feature stores, MLFlow.
- Experience with active learning/uncertainty sampling and human-in-the-loop systems.
- Stakeholder management and executive communication; ability to set vision and drive cross-org programs to measurable outcomes.
- Graph analytics/ML and entity-relationship labeling (rings/collusion).
- Experience with online experimentation and real-time decisioning.
- Track record building inclusive teams and developing senior ICs/managers.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.