Microsoft Senior Data Scientist 

India, Telangana, Hyderabad 

879667085

The M365 Core org in IDC plays a pivotal role in powering end user experiences around and platform capabilities for the M365 eco system.

Required Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 6+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• 4+ years of experience developing applications in the cloud using technologies such as SQL, Kusto, Databricks, Azure ML, Spark etc.

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 Qualifications:

• Ability to communicate complex ideas and concepts to leadership and deliver results.
• Experience in manipulating and analyzing complex, high dimensional data from varying sources to solve challenging problems.

• Identify data sources, integrate multiple sources, or types of data, and develop expertise with multiple data sources to tell a story and to compensate for missing data, identify new patterns and business opportunities, and communicate visually and verbally with clear and compelling data-driven stories.
• Hands on experience in creating and deploying Machine Learning Methods like Regression, Classification, Clustering, Dimensionality Reduction, Ensemble Methods, Natural Language Processing and Forecasting Methods.
• Creation of full lifecycle of predictive models, starting from analysis problem formulation, data unifications, model training & deployment. Identification of actionable & build alert system as per need.
• Identifying anomalies - involves watching user behavior to catch violations of terms of use, spotting unusual activities, building machine learning models to flag suspicious behavior early and prevent abuse.
• Building Fraud Detection models- identifying users who exceed normal behavior patterns, indicating potential fraud. Implement Machine learning models to recognize unusual transaction amounts or frequencies, helping to detect and stop fraudulent activities.
• Experiment (Control/Treatment) design & hypothesis testing and ensuring the decision criteria for the experiment are correctly reported and interpreted considering the statistical confidence & Significance --good to have.
• Transform formulated problems into implementation plans to develop forecast models to predict future trends and apply appropriate decision-making metrics, backed up with thorough exploration data analysis.
• Acquires and uses broad knowledge of innovative methods, algorithms, and tools from within Microsoft and from the scientific literature and applies his or her own analysis of scalability and applicability to the formulated problem.