Senior Data Scientist 

I’m a Senior Data Scientist at Scry AI with a solid foundation in machine learning, deep learning, and scalable software systems. With a Master’s in Computer Science from USC and years of hands-on experience, I’ve built and deployed data-driven solutions across diverse industries. My work spans building robust data pipelines, designing intelligent models, and deploying them at scale using tools like Python, Spark, AWS, Docker, and Kubernetes. I thrive in collaborative, agile environments where I can combine analytical thinking with real-world impact, and I’m always looking for ways to create smarter, more efficient systems.

• Redesigned existing build and release pipelines to increase code quality, reduce build time, and improve deployment efficiency.

• Designed and maintained observability infrastructure using Grafana, Prometheus, Loki, and Promtail, enhancing monitoring and reducing incident response time; provided on-call support and worked closely with cross-functional teams to resolve production issues.

• Played a key role in team operations—collaborated with globally distributed teams, conducted technical interviews, and partnered with marketing teams to deliver tooling and infrastructure supporting internal and external initiatives.

• Led end-to-end development and deployment of scalable backend modules using Python, Kubernetes, Docker, AWS (EKS, EC2, S3), and Jenkins; delivered client-side deployments, implemented horizontal/vertical scaling, Helm configurations, and robust CI/CD pipelines to support high-availability services.

• Built and integrated shared utilities and automation scripts to standardize workflows across repositories, improve pipeline efficiency, and reduce manual intervention; contributed quick PoCs and supported ML model training efforts.

• Created and integrated new modules and functionalities into an existing product to improve and enhance it further.

• Developed proofs-of-concept and demos for clients according to their requirements.

• Researched and explored the latest research advancements to implement and integrate them into the current product to improve the current state-of-the-art version.

• Assisted the professor in teaching, grading, and proctoring a class of 300+ students in a graduate-level course with a team of 16 teaching assistants and course producers.

• Created programming assignments and Exams, and held weekly office hours for students to guide and clear their doubts.

• Serving as the first line of support for customer technology to all faculty, staff, and students when using general-use classroom audio-visual equipment in any of the auditoria, classrooms, collaboration spaces, and computer labs across campus. 

• Guided and mentored fellow mentees in the following fields: Interviewing for a Job, Programming, Data Science/Computer Science Tools and Technologies

• Scheduled virtual mock interviews and sessions for explaining programming concepts

• Developed Spark - Scala modules to collect, transform, handle, and store about 300TB of client’s data from legacy on-premise systems like Business Objects Data Services SAP (BODS), IBM Integration Hub (IIB) and Oracle Golden Gate (OGG) on HDFS and AWS Cloud, enabling the client to analyze on the complete data and statistics to make business decisions

• Created 2 new project opportunities from client worth $50,000 by training 10 junior employees in Python and PySpark technology

• Increased the efficiency of the project and saved 20% time of the team by automating key repetitive tasks with Unix shell scripting 

• Reduced the cost of hiring temporary staff by an estimated 10% annually by developing Machine Learning and time-series models in Python on the client’s 5-year data to predict the number of children expected to attend E-Day-Care facilities located in California, USA