Microsoft Senior Data Scientist 

India, Telangana, Hyderabad 

779612201

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.

• 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.