Microsoft Logo

Microsoft

Senior Data Scientist, AI Infrastructure

Reposted 3 Days Ago
Be an Early Applicant
In-Office
Redmond, WA
143K-304K Annually
Senior level
In-Office
Redmond, WA
143K-304K Annually
Senior level
Lead end-to-end delivery of high-impact data science and AI solutions for AI infrastructure. Clean and prepare hyperscale datasets, build and deploy predictive, prescriptive, and generative AI models (including LLMs), implement prompt engineering and fine-tuning, and collaborate with stakeholders and engineers to drive adoption, measurement, and responsible AI practices.
The summary above was generated by AI
Overview

As a Senior Data Scientist, you will own end-to-end delivery of strategic data science projects and partner with customers and internal teams to design and implement advanced analytics and AI solutions that create measurable business impact. This hands on role blends deep technical expertise with consulting and stakeholder engagement, enabling you to influence decisions and guide adoption of data-driven strategies. 

The AI Infrastructure team builds, operates and optimizes one of the largest AI fleets in the world.  Our Data Scientists leverage data to inform everything from infrastructure planning to systems design to product feature tradeoffs.  You will be expected to work across a wide variety of subject matters and partnership levels to identify and drive action against the largest opportunities. 

The AI Infrastructure Data team is full stack owning telemetry collection, data infrastructure, processing, experimentation and measurement for a wide range of partner teams, systems and business processes.  Close collaboration with Data Engineers, Data Infrastructure SWE and SMEs are a day to day component of our model.  The team regularly interacts with hyperscale datasets, systems and challenges to deliver impact to the companies most important initiatives. 

At Microsoft, our mission to empower every person and every organization on the planet to achieve more guides how we partner with customers to deliver trusted, impactful solutions. With a growth mindset culture, we innovate responsibly and measure success by shared progress people, teams, and customers. Join us to do meaningful work that changes the world and helps shapewhat’snext for everyone.   


Responsibilities

Business Understanding & Impact 

  • Own delivery of complex, high-impact data science and AI solutions for strategic consulting engagements. 

  • Collaborate with stakeholders to define business problems and translate them into actionable AI-driven solutions. 

  • Develop project plans, assess risks, and ensure alignment with strategic objectives and ethical AI principles. 

  • Identify opportunities to leverage generative AI for business transformation and innovation. 

 
Data Preparation & Modeling 

  • Acquire, clean, and prepare large datasets for modeling. 

  • Build and deploy predictive and prescriptive models using modern machine learning techniques. 

  • Design, develop, and integrate generative AI applications (e.g., text, image, multimodal) into client workflows and solutions. 

  • Write efficient, maintainable code and ensure scalability for production environments. 

  • Implement prompt engineering, fine-tuning, and evaluation strategies for large language models and other foundation models. 

Insight, Communication & Enablement 

  • Present findings to senior stakeholders using compelling storytelling and visualizations. 

  • Simplify complex ML/AI concepts for diverse audiences to drive understanding and adoption. 

  • Document best practices for AI application development and share knowledge across teams. 

Collaboration & Consulting 

  • Act as a trusted advisor to internal teams and customers, ensuring solutions meet business needs. 

  • Promote responsible AI practices, including fairness, transparency, and explainability in model and application development. 

  • Stay current with emerging AI technologies, frameworks, and tools to continuously enhance solution capabilities. 


Qualifications

Required/minimum qualifications: 

  • 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 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 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 equivalent experience. 


Additional or preferred qualifications: 

  • Doctorate 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 Master'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 Bachelor'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 equivalent experience.  

  • Proven consulting and stakeholder engagement skills with proven ability to influence decisions. 

  • Proficiency in Python and SQL; experience with cloud platforms (Azure preferred). 

  • Knowledge of Responsible AI principles and ethical data practices. 

  • Experience with broader software engineering lifecycle practices, including version control, testing, DevOps, and production deployment of Machine Learning (ML) solutions. 

  • Experience with AI-assisted coding practices and specification-driven development. 

  • 1 to 3 years of Consulting (including System Integrator, Technical Consulting or Management Consulting) experience.  

  • Experience developing and deploying Agentic AI solutions 
    #AIinfra


Data Science IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 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 $188,000 - $304,200 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.

Similar Jobs

3 Hours Ago
In-Office
78K-117K Annually
Entry level
78K-117K Annually
Entry level
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Provide and coordinate nursing care in patients' homes, develop and update care plans, perform comprehensive assessments (including OASIS and med reconciliation), supervise aides/LPNs, document per policy, communicate with physicians and families, participate in staff orientation and quality improvement, and participate in on-call/weekend rotations.
3 Hours Ago
In-Office
40K-164K Annually
Junior
40K-164K Annually
Junior
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Provide non‑prescribing, in‑home comprehensive health assessments for Medicare Advantage and plan members: review history, reconcile medications, perform vitals and screenings, document findings, identify gaps and diagnoses, coordinate with primary care providers, educate members, address social determinants of health, refer services, and recognize/intervene in urgent situations to improve outcomes and care continuity.
3 Hours Ago
In-Office
22-30 Hourly
Entry level
22-30 Hourly
Entry level
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Provide front-desk and clinical support for IV therapy patients: collect vitals and specimens, prepare patients for exams and procedures, assist providers, document in the medical record, process prescriptions/referrals/authorizations, schedule injections/infusions, order and manage inventory, and perform diagnostic testing and lab tasks.
Top Skills: EcwEmrMs Outlook

What you need to know about the Los Angeles Tech Scene

Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.

Key Facts About Los Angeles Tech

  • Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
  • Key Industries: Artificial intelligence, adtech, media, software, game development
  • Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
  • Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account