Helping build AI-powered control systems for the industrial sector, enabling industrial facilities to automatically learn and improve over time with a specialization in improving the energy efficiency of data center operations which also leads to less carbon emissions. I work on the backend services and APIs that power the data platform, which includes data ingestion, data processing, and data storage. I also work on the data infrastructure and machine learning infrastructure. Laid off abruptly to organizatinal restructuring to get more runway.

Helped develop an AI-powered platform that connects brands with content creators. Worked on the frontend and backend of the platform using React, Next.js, Typescript, Node.js, and Postgres.

Co-founded a startup focused on ESG due diligence software for asset management firms. Despite having an advisor and early pilot customer, we faced significant challenges related to data integration and product scalability, leading to the project's eventual abandonment in February 2024. This experience taught me valuable lessons about product-market fit, team dynamics, and the importance of persistence in the face of setbacks.

Utilized career break to contribute to IT sector initiatives, contributing to local tech startups and tech education. Directed a REST API development workshop for 15 TUMO students, producing a 100% project completion rate and fostering advanced Java, Spring Boot, API integration & development, and Docker skills. Developed and led a masterclass on Prompt Engineering at the Armenian Code Academy for 20+ participants. Led a backend team of 3 in developing a Streamlit-based ESG market intelligence app, which included MySQL database design and implementing client-side APIs to aggregate and wrangle data from ESG data sources and the SEC.

I played a pivotal role in the development of the Luminai Refinery Operations Advisor, which generated over $4 million in revenue while optimizing customer refinery operations by an average of 17%, leading to substantial cost savings. As part of a team, I helped drive Agile collaborations in creating a multi-tenant SaaS industrial AI platform, currently scaling to serve 20-30% of global oil refineries, with a deployment that ingests streaming data from over 130,000 sensors via Apache Flink. My contributions include developing backend APIs and services in Java using the Spring framework and Postgres, as well as architecting and launching a scalable RESTful Reporting API that handles over 5 million rows in PostgreSQL, reducing report generation time by 50% and enhancing data extraction efficiency. Additionally, I improved the throughput and reliability of a critical Apache-Flink based real-time streaming pipeline by 40% through comprehensive documentation and rigorous testing. Beyond my technical work, I also led initiatives in on-campus recruiting, mentoring interns, and supporting their projects.

I co-founded a B2B SaaS startup within Untapped Ventures, a startup studio in Los Angeles. During this period, I researched corporate innovation by developing foundational business models to assess the feasibility of bringing various minimum viable products to market. I conducted user discovery interviews with corporate innovation leaders and teams, which provided valuable insights into market needs. Additionally, I applied lean methodology to build and validate these business models, ensuring that our product development efforts were aligned with real-world demands. This experience offered deep insights into startup dynamics, product development, and the challenges of launching new ideas in a competitive market. Ultimately our founding team broke off to pursue other opportunities. I started my master's degree in Computer Science at Georgia Tech in January 2021.

After graduating, I gained valuable experience as a data scientist from October 2019 to July 2020, working both as a freelancer and at a local startup. During this time, I developed and quantified 80 unique qualitative metrics for a dataset of 2,000 video advertisements, and applied machine learning algorithms like Decision Trees, Random Forest, and Apriori to analyze associations, optimize ad performance, and create visualizations for short-form video ad insights. I also led predictive analyses for freight and logistics data, collaborating with various local businesses in the sector.

Specialization in Computing Systems. Relevant coursework includes; Advanced Operating Systems, Computer Networks, High-Performance Computing (HPC), Machine Learning for Algorithmic Trading, Advanced Internet Systems, Distributed Computing, Graduate Algorithms

Relevant coursework includes; Advanced Econometrics, Principles of Data Science, Game Theory, Behavioral Economics, Advanced Information Economics, Financial Theory.