Does envisioning, innovating & transforming the employee experience across Microsoft’s global workforce excite you? Are you passionate about the future of work, harnessing the potential of state-of-the-art technologies like Artificial Intelligence (AI) /Generative AI and Machine Learning? Do you want to witness and be a part of the transformational and visionary journey that inspires our business partners and stakeholders to navigate through digital transformation? If so, Microsoft Digital (MSD) team is an excellent place for you to thrive & grow your career.

*Microsoft Digital (MSD)’s * mission is to power, protect, and transform the employee experience at Microsoft across the globe.  Come, build community, explore your passions, pursue your AI and ML aspirations, do your best work and be a part of the team within Microsoft’s Data Platform & Growth (DPG) organization and Experiences & Devices (E+D) division. Microsoft Digital (MSD), is the team that innovates, creates, and delivers the vision for Microsoft’s employee experience, human resources, corporate and legal affairs, global real estate products, and runs Microsoft’s internal network and infrastructure, plus builds campus modernization and hybrid solutions. You will leverage Gen AI, AI, ML, and other topical and latest technologies to focus on empowering Microsoft employees with the tools and services that define both the physical and digital future of work.  

Microsoft’s mission is to empower every person and every organization on the planet to achieve more, and we’re dedicated to this mission across every aspect of our company.  Our culture  is centered on embracing a growth mindset and encouraging teams and leaders to bring their best each day. Join us and help shape the future of the world.   

Job Purpose   

We are looking for an experienced Senior Data Scientist, who has hands-on proficiency in designing, developing, and deploying Machine Learning/Artificial Intelligence solutions for our Business Partners. We are looking for individuals who are thought leaders in the realm of Data Science, have thorough understanding of Statistical & Stochastic Modeling, Neural Networks, Deep Learning, RNNs, CNNs, Foundation Models (SLM, LLM) & Traditional ML Models, and can drive results by leading from the front while also mentoring the team and other Data Scientists within the organization. The ideal candidate will play a critical role working with other senior Product Managers, Software Engineers, and Architects across Microsoft to identify opportunities, collaborate and deliver impact. You will be working on curating, designing, architecting, developing, and deploying AI and ML solutions that drive cost and business efficiency, and are futuristic!

 #MSD  

#MSDJOBS  

#EEJOBS 

#DataScientist

#AIML

#GenAI

Responsibilities

• Elicit, design, and develop scalable, reliable, cloud-native AI/ML products – Foundational & Traditional ML Models.

• Be inquisitive, understand data & data imputation techniques, perform hypothesis testing, evidence based statistical & stochastic modeling, analysis & insights and able to find/discover the story in the data sets and provide a coherent narrative about key data insights.​ Transform the insights into intelligence.

• Apply best practices of AI/ML model development, leverage relevant libraries/APIs, feature engineer, principal component analysis, choose the right model for a given domain/business problem context.

• Write performance & cost-efficient modular code and drive end-to-end life cycle of ML Model development to solve complex problems and create innovative solutions. 

• Communicate effectively with stakeholders and present technical vision and solutions to large audiences. 

• Provide technical guidance and mentorship to the team and foster a culture of collaboration, excellence, and growth mindset.

• Rapid agility with Proof of Concepts, especially with emerging technologies, concepts and frameworks in AI and ML.  

Qualifications

Required Qualifications:  

•  Master’s degree in computer/data science/analytics/machine learning, or Engineering, or equivalent work experience. 

• Strong foundation in data and at least 7 years of experience in Data Science/AI/ML development, with a proven track record of delivering highly scalable, observable, and secure AI products. 

• Data Storytelling.

• Technical Proficiency & Hands-on Experience in Python, ML Libraries: scikit-learn, OpenCV, Keras, Scikit Learn, TensorFlow, Pillow, Torch Vision, Kats, Prophet, ARIMA, Seaborn to name a few​. Well versed in Natural Language Processing, Traditional & Foundation Models (LLM, SLM), Opinion & Sentiment Analytics, Forecasting, Recommendation System, Anomaly Detection, Dynamic Pricing, XGBoost, Random Forest, Ensemble Modeling Techniques, Markov, CART, Integer Linear Programming to name a few. Hands on experience on Azure ML Platform, Semantic Kernel, RAG, LangChain & Cognitive Services is nice to have.

• ​Contextual Understanding of the Business-Problem, ​Fail-Fast & Experimentation approach to bring structure & meaning to large quantities of formless data, turn Data into insights & insights into intelligence enabling business partners to make strategic & timely decisions. ​

• Understand, curate strategic business transformations and innovation initiatives deeply. Translate Business Issues and requirements into ML models. ​Augment value propositions for business through AI Interventions – AI strategies, interventions, programs, and engagements. Partner with Business/PM Stakeholders for Demand Generation​.

• Navigate through Data Science Lifecycle, Statistical Model Building - Descriptive, Predictive, Prescriptive, AI/ML System Design & Architecture, Sampling, Feature Engineering, Dimensionality Reduction, Principal Component Analysis, Supervised, Unsupervised & Reinforcement Learning ML Techniques & Models. ​

• Introduce, Implement & Integrate AI techniques with Data Semantics (Contextual Understanding), deliver models in testable units of work to solve complex business problems and achieve strengthened value proposition. Being adept and adheres to ML Deployment Strategies as relevant.​

• AI/ML Hygiene: Reduce False Positives, Identify Spurious Variables, Boost Model Accuracy, Deal with Concept Drift & Periodic validation of ML Models, Reduce MLDebt.​

Additional qualification that will be a bonus  

• Understanding of Responsible AI

• Working knowledge of MLOps & LLMOps

• ML Deployment frameworks

• Azure Cognitive Services, GitHub Co-pilot

• Microsoft Fabric/Purview

Non-Technical skills  

• Problem solving - Ability to clearly understand problems, decompose them into smaller problems; and technical articulation skills so that it is easy for the team to collectively solve.  

• Creative, Curious/Inquisitive & Associative Thinking : ​ A desire to go beneath the surface of the problem, find the questions (how’, ‘what’, why’, ‘when’) at its heart and distill them into a very clear set of hypotheses that can be tested & validated. 

• Ability to work both independently and collectively in a fun team environment with minimal supervision. 

• Good communication and stakeholder management skills 

• High capacity to learn and adapt to new technologies and engineering processes quickly. 

*Location: * We are hiring in the following locations: Hyderabad, Bangalore, Noida India.

Microsoft is an equal opportunity employer. Consistent with applicable law, 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 and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations (https://careers.microsoft.com/v2/global/en/accessibility.html) .