Microsoft Senior Data & Applied Scientist 

India, Karnataka, Bengaluru 

465474389

The Product

and multi-modal AI rich experiences

Power Pages’towards 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 proven track record of shipping at-scale AI-enabled intelligent systems to drive vision and innovation for PSenior Data &, you will beexecuting in

Required Qualifications

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND3+ years related experience (e.g., statistics, predictive analytics, research)

• Master's Degreein Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND2+ years related experience (e.g., statistics, predictive analytics, research)

• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND2+ years related experience (e.g., statistics, predictive analytics, research)

• OR equivalent experience.

Preferred Qualifications

• Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND3+ years related experience (e.g., statistics,predictive analytics, research)

• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND3+ years related experience (e.g., statistics, predictive analytics, research)

• OR equivalent experience.

• +years experiencewriting production code as well as deploying andmaintainingshipped models over time.

• 3+years experienceworking on deep learning architectures specifically with Natural language-based models, vector databases and graph databases

• A publication record in top AI venues will be considered a plus.

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.

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