- Leading data-oriented projects based on clients' needs, including work on data migration, deployment of prediction algorithms to the cloud, automating data-flows, and integrating databases into Sharepoint-based applications.- Focused on migration of SharePoint solutions from various On-Premise versions to SharePoint Online, encompassing all aspects of the application architecture: UI, Database, Backend (Custom WebParts)- Experienced in coding for each part of the development stack, including Frontend (using JS), API Development (Azure), Backend Development (Python), and Databases (SQL + NoSQL)

- Development of a multi-dimensional “risk score” for app users.- Integrated the risk score algorithm into an application built on the Microsoft stack – a SharePoint frontend that used custom JS Web Parts to send information to backend Azure services. The relevant data was maintained on an Azure Storage account using the Blob and Table storage mechanisms.- Designed a Reinforcement Learning (RL) algorithm from scratch to provide users step-by-step guidance to improve their health outcomes.- Investigated, cleaned, and aggregated previously-untouched engagement data for 80,000+ users.- Improved performance of existing blood glucose and blood pressure prediction algorithms.- Developed a Content Recommendation algorithm for educational content within the app, based on a combination of collaborative filtering and knowledge-based systems.

- Implemented semi-supervised clustering in R to classify cancer patients into sub-types.- Applied neural networks (TensorFlow) to perform text analysis of cancer research.- Built a standalone R Shiny app for deployment of the above TensorFlow model. - Developed a standalone app for Perthera clients to find matching clinical trials in their area.- Built custom back-end solution using Microsoft Azure and Data Verse that provided storage for a full-stack Microsoft app with frontend in SharePoint.

- Project and Client Management: Was the primary point person responsible for engagement delivery, managing project timelines, workstreams, deliverables, and team members while maintaining client relationships across multiple key stakeholders (internal and external)- Mentorship and Training: Helped develop and mentor junior analysts and data scientists through on-the-job, project-based training- Software Development: Wrote code to generate answers to analytic inquiries. Performed analytic activities (test design/evaluations, incrementality/attribution, journey analytics, etc.) to generate insights. Built core data science products, including statistical models, complex reports and/or data visualizations. Employed modern data science techniques, such as machine learning, deep learning, and reinforcement learning.- Utilized procedures to feature engineer, move data, and automate products on top of latest data science and modeling advances.