Harpreet Shoker

Microsoft Cloud + AI group

• Improving Azure's commerce experience for customers by leveraging data analytics.
• Gathering requirements, identified gaps,documenting in Azure DevOps, reviewing with stakeholders.
• Using Agile/Scrum project management principles for product development.
• Working with Engineering to capture usage data for Microsoft Azure's commerce products.
• Analyzing data to find key insights, applying data driven approach to product development (prioritizing product backlog etc.).
• Extracted,integrated and transformed data from multiple sources using SQL,KQL and DAX.Built data pipelines,data models,designed metrics for business and maintained reporting data models.
• Storytelling with data, developing Power BI reports and dashboards

Capstone 1 - Financial Fraud Detection(Machine Learning)

• Analyzed and classified financial fraud transactions into genuine or fraud using different Machine learning models including logistic regression, Random Forest and XGBoost

Capstone 2 - Plant Disease Detection (Deep Learning)

• Developed algorithm that can accurately classify and diagnose a disease based on a crop image for 38 different classes with dataset containing 87K images of different leaves.Implemented Residual Neural Network with accuracy of 99.2% using Pytorch.

• Mastered Machine Learning, Artificial Intelligence, Algorithms, Design and Data Analysis, Software Product and Process Evaluation, and Big Data.
• Thesis Paper (Capstone) “Hierarchical Risk Parity (HRP) Optimization Approach to Reduce Portfolio Risk” - Research proposes HRP machine learning algorithm for financial portfolios construction.

• Participated in cross-functional collaborations with business/technology teams to develop insightful analytical solutions
• Contributed to Agile development environment including scrum meetings/reviews; harnessing insights to enable teams ability to realize business goals/targets
• Boosted company growth by acquiring 20% new customers through identifying key product features by analyzing customer data
• Build out data and reporting infrastructure from ground up and wrote SQL to provide real time insights into business KPI's
• Designed and implemented A/B experiment for products that improved product by 25%.
• Automated manual regression test scenarios using Sikuli, Selenium IDE, and Codeception.

• Conducted investigations to resolve/report data discrepancies as well as drive effective data testing
• Created various ad hoc report by collecting data
• Contributed to early stages of data collection by analyzing both structured and semi structured data, discovering anomalies to inform team about product loopholes through disseminating large amount data.
• Triggered monthly labor reduction by 50% by developing/owning reporting for entire program with Python and SQL.

• Validated data by gathering business/functional requirements and leveraging expertise in back-end testing using Teradata SQL and database structures.
• Governed defect tracking; fixing application defects and data quality issues within agreed SLA timeframes.
• Used SQL Assistant front end tools to issue SQL commands matching business requirements to Teradata RDBMS.
• Responsible for Extracting, Transforming and Loading data from various sources using BTEQ ,FastLoad,MultiLoad and loaded into Teradata Warehouse.