Data & Applied Scientist II
Microsoft
Data & Applied Scientist II
Bangalore, Karnataka, India
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Overview
Microsoft is a company where passionate innovators come to collaborate, envision what can be and take their careers to levels they cannot achieve anywhere else. This is a world of more possibilities, more innovation, more openness in a cloud-enabled world. MCAPS is Microsoft's unified commercial organization that brings together sales, partners, industry, and customer success teams to drive business impact at scale. It is designed to accelerate customer outcomes through AI-powered solutions, strategic partnerships, and deep industry expertise. Microsoft is considered one of the leaders in Software as a Service in the world of business applications and this organization is at the heart of how business applications are designed and delivered.
We are looking for a Data & Applied Scientist II to join our team! As a member of the Customer Experience Data Science organization at Microsoft, you will help us accelerate the company’s own AI transformation. You will have the opportunity to partner directly with the engineering and product management groups responsible for managing the Dynamics 365 applications that power Microsoft’s sales, marketing, and support platforms. You will apply advanced analytics, statistical modeling, machine learning and GenAI tools to uncover insights, drive action and deliver innovative solutions for complex business challenges.
This role offers the opportunity to:
- Collaborate across a diverse team of data scientists, engineers, and product managers
- Deepen your expertise in the evolving AI and ML landscape
- Drive meaningful impact for thousands of Microsoft sales, marketing and support platform users
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.
Qualifications
Required/Minimum Qualifications (From Role Library, plus any other HM-determined qualifications)
- Bachelor’s degree in data science, Mathematics, Statistics, Computer Science, or related field AND 5+ years related experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR master’s degree in data science, Mathematics, Statistics, Computer Science, or related field AND 4+ year(s) related experience
- OR Doctorate in Data Science, Mathematics, Statistics, Computer Science, or related field AND 3+ year(s) related experience
- Expertise in Python , PySpark, and SQL, LLMs
- Experience in Spark and ability to write/maintain/understand declarative Spark code and to cleanly write and maintain SQL. Knowledge of finer operational aspects of Spark such as setting optimal cluster size, executor memory, number of executors etc. and experience in Azure Synapse/Databricks (or similar) is a bonus.
- Exposure to ML development platforms such as Azure Machine Learning, Azure AI Foundry + Azure OpenAI
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/Additional Qualifications (Optional, at HM discretion)
- Build and deploy end-to-end ML pipelines and GenAI solutions for both batch and real-time use cases, ensuring scalability and reliability.
- Apply MLOps and AIOps best practices including model versioning, prompt versioning, experiment tracking, environment management, and understanding of CI/CD automation on cloud platforms (AWS, Azure, GCP).
- Manage environment dependencies and containerization (Docker/Kubernetes) for reproducible, scalable deployments in any of the cloud platforms (AWS, Azure, GCP etc.).
- Exposure to some ETL pipelining frameworks such as Azure Data factory, Apache Airflow etc.
- Expertise in designing and implementing Generative AI pipelines (e.g., RAG systems, domain/task-specific finetuning)
- Experience in managing codebases in Git, creating release pipelines on CI/CD frameworks like Azure DevOps, Jenkins etc. along with creating/managing Python deployment scripts
Responsibilities
Responsibilities:
- Work with key stakeholders to understand the underlying business needs and formulate the needs into discrete, manageable problems with well-defined measurable objectives and outcomes.
- Transform formulated problems into implementation plans by defining success metrics, applying/creating the appropriate methods, algorithms, and tools, as well as delivering statistically valid and reliable results.
- Write robust, reusable, and extensible code to support analysis and modeling.
- Develop new ML or GenAI based models using advanced statistical and ML techniques.
- Lead the evaluation of various GenAI based solutions, diagnosing issues and identifying root causes to support potential fine-tuning or reinforcement learning based fixes.
- Use AI-powered tools in your daily work to accelerate coding, analysis, and other tasks.