Senior Data Scientist - Azure Storage

Are you passionate about data, problem solving, distributed systems, and being on the forefront of driving innovations and efficiencies at a massive scale? If so, the Microsoft Azure Storage team might be a great fit for you.

Azure Storage, a cornerstone of Microsoft Azure, offers a robust and scalable platform for global customers to store and manage their data. With a focus on performance, reliability, durability, and security, Azure Storage provides a suite of services including Blob Storage, File Storage, Queue Storage, and Table Storage, each designed to meet the diverse needs of our customers' modern data workloads. We have grown tremendously, with several Exabytes of data stored on our platform, and are designing and building systems for Zettabyte scale to support the anticipated demand for the coming years.

As we continue to innovate and expand our capabilities, we are looking for a Senior Data Scientist- Azure Storage who can leverage data to solve high-impact business problems. In this role, you will have the opportunity to use machine learning techniques and statistical analyses to experiment with data and push the boundaries of how much value we can create for both our customers and the business. You will be able to use the insights you gain to help shape and strengthen Azure Storage's technical and business strategy, as well as to have a direct impact on storage efficiency by collaborating with our brightest engineers across the Azure stack to deliver end-to-end results.

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. If you share our values, love working with data, and want to solve some of the most exciting challenges on a massive product like Azure storage, this could be the perfect position for you.

Responsibilities:

• Design and implement predictive and prescriptive models to personalize learning content based on user roles, skills, and context.
• Collaborate with product managers, engineers, and user experience (UX) researchers to translate business needs into analytical solutions.
• Develop scalable machine learning (ML) pipelines and integrate them into Storage's backend systems.
• Conduct experiments to evaluate model performance and iterate based on feedback and telemetry.
• Evangelize data science best practices across the team and mentor other data scientists.
• Explore and apply generative artificial intelligence (Generative AI) techniques (e.g., large language models (LLMs), prompt engineering, fine-tuning) to enhance learning experiences, automate content generation, and improve semantic understanding.
• Knowledge and implementation of an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
• Write efficient, readable, extensible code from scratch that spans multiple features/solutions. Develops technical expertise in proper modeling, coding, and/or debugging techniques such as locating, isolating, and resolving errors and/or defects.

Qualifications:

Required 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 techn
• 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 tec
• OR equivalent experience.
• 3+ years of applied data science experience, including building and deploying machine learning models at scale.
• 3+ years of skilled in Python, R, or Scala, with SQL capabilities and hands-on experience using ML frameworks like scikit-learn, PyTorch, and TensorFlow.
• 3+ years proficiency in Generative AI models such as GPT (Generative Pre-trained Transformer), T5 (Text-to-Text Transfer Transformer), and BERT (Bidirectional Encoder Representations from Transformers), using frameworks like Hugging Face and OpenAI.
• 3+ years of demonstrated success in leading experimentation (A/B testing and causal inference), collaborating across cross-functional teams, and communicating technical insights clearly to non-technical audiences.

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:

• 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.
• 1+ year(s) experience working with cloud-based technologies and big data solutions (e.g., Hadoop, Spark).
• 1+ year(s) exposure to semantic search, knowledge graphs, or Copilot integration, and p roficiency deploying solutions in Azure Services and Managing Azure Subscriptions.
• 1+ years of analytical skills with a systematic and structured approach to software design of demonstrated ability to lead projects independently and influence cross-functional teams, supported by stakeholder management and communication skills.

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: ;br>
Microsoft will accept applications for the role until October 15, 2025

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form .

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

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