Data Science Stack Developer

VEDANT MISRA

+1-814-***-**** *******@***.*** linkedin.com/in/ved-dev github.com/this-ved-dev www.ved.dev EDUCATION

The Pennsylvania State University, University Park Aug 2024 – May 2026 Master of Science in Computer Science & Engineering Teaching Assistant – BA 840: Business Data Management, Smeal School of Business Mukesh Patel School of Technology Management & Engineering, NMIMS June 2019 – May 2023 Bachelor of Technology in Computer Engineering (Hons. Data Science & Analytics) GPA: 3.73/4 TECHNICAL SKILLS

Programming:Python, Java, C/C++, PHP, SQL, Go, TypeScript, Shell, Django, ReactJS, Angular, Node, Express DB & Cloud: MySQL, PostgreSQL, NoSQL, MongoDB, DynamoDB, Firebase, Snowflake, Redshift, AWS (EC2, RDS, OpenSearch, Glue, QuickSight), GCP, Azure, Docker, Kubernetes, Terraform, Jenkins, Ansible, IPFS Data Science: Tableau, Power BI, SAS Viya, TensorFlow, PyTorch, Keras, Scikit-learn, SAS, MATLAB, R Certifications: AWS Developer-Associate, Google Data Analytics, IBM Full Stack Developer, SAS VBA. EXPERIENCE

Business Technology Solutions Associate, ZS Associates June 2023 – June 2024

• Reduced pharmacology simulation costs by 60% and execution time from 5 days to 3 hours by implementing a MATLAB workload parallelization framework using PySpark, Athena, AWS EC2 Spot and On-Demand instances.

• Automated EC2 cluster provisioning for 10,000 vCPUs with Ansible, Node.js, and Shell, cutting spin-up time from 110 to 2 minutes using custom AMIs.

• Built a search and recommendation engine for clinical data transfer using OpenSearch and GPT-4, enabling dynamic query generation, rapid data indexing, and efficient retrieval.

• Designed a custom DQ dashboard in QuickSight, integrating Athena, S3, and Lambda to monitor vendor data com- pliance and integrity, reducing error detection time by 35%. Data Science Intern, SAS Institute Aug 2022 – May 2023

• Delivered a transport analytics POC, resulting in 15% cost savings through optimized routes and demand forecasting.

• Optimized premium rates & active insurance policies for clients using SAS PROCOPT, reducing VAR by 36%.

• Developed SAS-VIYA visualizations into a Customer Intelligence application using ReactJS, enabling KPI tracking and streamlined portfolio management, resulting in a 40% reduction in operational costs for the BFSI sales team.

• Analyzed fraudulent insurance claims & customer-churn data to device ML-based statistical models reducing false positives by 68%.

Technology Consulting Intern, Ernst & Young LLP May 2022 - June 2022

• Evaluated client IT portfolios using process mining to identify automation opportunities, estimating up to 70% enter- prise IT automation and a 22% reduction in infrastructure and application maintenance costs.

• Streamlined identity access provisioning by integrating Azure Active Directory with Citrix XenApp, enabling efficient and secure policy implementation with projected savings of 50 FTEs. Full Stack Developer, The Experitos Studio June 2021 - Aug 2021

• Curated a cloud-native data-driven platform to provide actionable insights to entrepreneurs using predictive analytics.

• Implemented RESTful SpringBoot APIs for data ingestion & analytics, integrated with a no-code interface, Bubble.io.

• Containerized XGBoost and regression models with Docker and deployed the system on Kubernetes, leveraging hori- zontal scaling, load balancing, and CI/CD pipelines for seamless feature integration and high availability.

• Achieved 92% accuracy in the Start-up-Growth Index, 85% accuracy in the Start-up-Launch Index, and 88% accuracy in Investment Readiness Analysis, providing real-time, actionable insights to entrepreneurs. PROJECTS

Roommate Compatibility DApp. Adopted Agile methodology to engineer a decentralized MERN application with smart contracts for secure & transparent housing agreements. Led the implementation of BERT summarization & K-Means clustering, analyzing 5,560 profiles with 95.43% accuracy, refining processing times & housing allocation. LEADERSHIP & ACHIEVEMENTS

• Presented at the IEEE Bombay Section Signature Conference (December 2022), achieving 98% accuracy in lung cancer prediction and 85.71% in NSCLC classification using 13 data mining techniques, published in IEEE Xplore.

• Secured 2nd place in Northrop Grumman’s Innovation Hack Week by developing a real-time object detection system integrating Grounding DINO and YOLOv7 models.

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