Microsoft Data & Applied Scientist II 

India, Karnataka, Bengaluru 

175763436

The Product

low-code/no-code development models to accelerate their digital transformation ambitions. Power Platform is a strategic new growth area for Microsoft, but more importantly, it is a disruptor technology that is giving “Citizen access” to broader set of users in an enterprise, to create next generation of business productivity software via radically simplified experience and without requiring extensive and costly training. It is transforming careers of ‘citizen developersmaking pro-developers far more productive and helping IT finally innovate at the pace that their businesses expect. To boost Power Platform to scale to, we are investing in Power Pages– a product within Power Platform suite currently used by customers to enable collaboration with users both internal and external to their organizations. We are early in our journey to innovate on Power Pages product and shape it into a thriving standalone customer-facing business to drive incremental revenue and value for Power Platform.are innovating and iterating at a very rapid pace. To further accelerate the momentum in this space – bringing AI powered experiences to the business application space changing how people work - we continue to grow our investments of generative AI capabilitiesand multi-modal AI rich experiences.

We are a very dynamic and passionate team that fully embrace the build-measure-learn iterative development approach. We work towards the common goal of building a product customers love. As a natural part of our product design and development process we are working very closely with customers as well as listening to usage telemetry and other key signals which allow us to consistently evolve based on customer demand and adoption patterns. Deep collaboration across PM, Design, Engineering, and Science is a given and all disciplines play important roles as part of the product development process.

Power Pages’and rich. We foster a culture of diversity, collaboration, and innovation, valuing everyone's unique perspectives and contributions. Our agile, start-up-like environment encourages out-of-the-box thinking and empowers each team member to contributetowards our shared mission of delivering a highly innovative, AI powered experience that is positioned to fundamentally change what business applications look like in the future.

Senior Data &who can bring deep applied science experience and a proventrack recordof shipping at-scale AI-enabled intelligent systems to drive vision and innovation for P. As aSenior Data &, you will beexecuting inan exciting and fast-paced environment, collaborating closely with teams across the company, including Microsoft Research and various product groups. You will work as part of an organization that brings together talent in the areas of large language models, deep learning, information retrieval, software engineering, and responsible AI. We value and encourage diversity in the belief that it leads to both great workplaces and great products.

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.

Required Qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field

• Master's Degree 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 tec

• Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical tec

• OR equivalent experience.

• + year(s) experience developing end-to-end Machine Learning systems.

Preferred Qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Operations Research, Computer Science,

• R related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)

• 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)

• 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.

• Understanding of public cloud design patterns and considerations in the areas of Distributed Storage Systems, Big-Data, Data Mining, Information Retrieval.

• idealcandidate would:

• Have good interpersonal, oral, and written communication and presentation skills, and the ability to communicate complex findings simply.

• Enjoy discovering and solving problems, proactively seeking clarification of requirements and direction, being a self-starter who takes responsibility whenrequired.

• Be able to explore different directions for analyses and be able to quickly adapt and change direction based on the data.

Responsibilities

• in the area ofLarge Language Models, Natural Language Processing, Machine Learning and Deep Learning.

• Push the boundaries of AI platforms through innovation and partnership.

• Develop and deploy conversational and language understanding models at scale.

• Following and advancing best practices for Responsible AI and Privacy Preserving Machine Learning.

• Collaborate closely with Microsoft Research and product teams to create the next generation of AI innovation in our products and services. · Embody ourcultureand

• and