Jayashree Dommara

Coordinated 28 projects by collaborating with clients to define project scopes, ensure data quality, and align technical feasibility. Mentored student teams, provided technical guidance, and managed communication.

Scraped and unified data of 3000+ researchers and 100+ grants into a Dash-based web app powered by LLMs to streamline the grant tracking, and matching process. Leveraged RAG for curating matches of grants and research.

Created a predictive model to rank the new sales request item to efficiently plan & prioritize the sales request. Classification models used: Decision Trees, Random Forest, Light GBM.

•Cyber Resiliency: Enhanced the UI / UX of 3 cyber resiliency dashboards by including 15 new KPIs of business continuity and cyber resiliency plans using Power BI DAX to increase transparency for the business stakeholders. •Commodity Trading: Supervised the development of an internal trader dashboard to monitor the trade metrics of ~10 commodities across the globe, coordinating with stakeholders from 3 different business units. • Spearheaded 8 decision scientists in delivery, handled project approvals, maintained the internal project & revenue tracking system, and facilitated client engagement for the Data science Team at Mu- Sigma. • Conducted 15+ decision scientist interviews across different universities and optimized the candidate screening process by revamping the testing methodology at Mu- Sigma.

Delivered end-to-end data-driven solutions to a Fortune 10 firm in the following projects: •Sequence Optimization: Developed a solution using Python to provide optimal drilling & completions schedule for 50+ wells using a genetic algorithm leading to a reduction in manual effort & a financial outcome of ~$120 MM. •Price Prediction: Automated the marine vessel price prediction by leveraging machine learning models to make efficient contracting decisions for the supply chain management team to save ~$50MM annually. •Database Design: Designed the data model, and schema for RDBMS using SQL to store 8 years of past data along with real-time data from 100+ sensors(pumps) leading to a 40% reduction in data latency in the Python-based UI. •Digital Twin: Created an interactive Python-based web application to perform univariate and bivariate data cleaning on well sensor data to predict well sanding events of 60+ wells and prevent catastrophic damage.

Courses: Machine Learning in Finance (Python), Big Data Analytics in Finance (AWS, R), Enterprise Database Mgmt. (SQL), Decision Analytics, Big Data Infrastructure (AWS), Supply Chain Analytics (Python), Financial Data Mgmt (SAS). Projects: •NFT Analysis: Analyzed the sales of the Ethereum-based AZUKI NFT by creating a dashboard in Flipside using SQL queries. Stored the Flipside NFT data in MongoDB and connected it to Knime to create an analysis workflow. Tech: SQL, Flipside, Knime, MongoDB •Employee Churn Analysis (Ball Corporation): Identified KPIs influencing operations, and employee churn for 16 plants & provided recommendations to achieve operational excellence with email alerts in Power BI, providing real-time insights for strategic decision-making •Property Valuation: Researched and implemented a housing valuation model for COOK County, accounting for 20+ variables through a Light GBM machine learning model approach and achieved 10% lower MSE than the benchmark

Courses: Calculus, Linear Algebra, Ordinary Differential Equations, Numerical Methods, C Programming