CV

Namit Shrivastava

namo507@umd.edu
240-476-8513
College Park, Maryland, US

Summary

High performance AI and Data Engineer with 2 years of experience shipping production-grade ML systems and scalable ETL pipelines on Azure and AWS. Specialized in deploying RAG architectures, geospatial analytics, and high-throughput microservices. Currently pursuing MS in Survey Data Science at the University of Maryland.

Education

  • Master of Science, Survey Data Science (Data Science Track)
    2026-05
    University of Maryland, College Park
    GPA: 3.814/4.0
    Courses: Survey Methodology, Machine Learning, Data Privacy, Natural Language Processing, Causal Inference, Geospatial Data Analysis
  • Bachelor of Engineering (Honours), Civil Engineering; Minor in Data Science
    2024-07
    Birla Institute of Technology and Science (BITS Pilani)
    GPA: 3.327/4.0
    Courses: Data Structures & Algorithms, Machine Learning, Database Systems, Statistics, Linear Algebra, Probability Theory

Work Experience

  • Graduate Research Assistant
    2026-01 - 2026-05
    Social Data Science Center, University of Maryland
    Engineered automation and data infrastructure for university data repository.
    • Engineered Python automation suite interacting with CKAN REST API to manage lifecycle of 18 datasets ensuring 100% resource accessibility and data integrity
    • Architected scalable data taxonomy for university repository transforming flat catalogs into hierarchical thematic groups, improving search discoverability by 35%
    • Implemented bulk metadata update scripts reducing manual maintenance overhead by 90% and ensuring strict schema compliance across the repository
  • Teaching and Graduate Assistant
    2025-02 - 2026-05
    Joint Program in Survey Methodology (JPSM), University of Maryland
    Translated complex data privacy frameworks into actionable learning modules and optimized course operations.
    • Translated complex data privacy frameworks into actionable learning modules for 23 graduate students
    • Optimized and coordinated learning operations using Asana, reengineering Canvas LMS infrastructure with automation scripts reducing course setup time by 40%
  • Research Assistant
    2025-05 - 2025-12
    Institute for Social Research, University of Michigan
    Built scalable geospatial ETL pipelines and composite imputation models for longitudinal demographic analysis.
    • Built scalable geospatial ETL pipeline aggregating multi-source demographic data (FCC, ACS, CDC) for 129,572 U.S. census tracts
    • Developed composite imputation models recovering 28.6% of critical dataset rows and resolving complex missingness patterns for longitudinal analysis
    • Designed automated Data Quality framework using Moran's I statistics to detect spatial autocorrelation anomalies, flagging 15% of tracts for review
    • Synthesized disparate government datasets into a unified schema enabling identification of statistically significant rural health trends
  • Machine Learning Engineer
    2024-01 - 2024-06
    Legistify Services Private Limited
    Architected and shipped production-grade trademark search engine and OCR pipelines on Azure.
    • Architected and shipped production-grade trademark search engine processing 2.4 million images using FastAPI and Faiss vector embeddings
    • Reduced query latency by 60% by optimizing HNSW indexing parameters and implementing asynchronous microservice architecture
    • Deployed scalable OCR pipelines on Azure Cognitive Services processing 50,000 daily legal documents with 95% bilingual text extraction accuracy
    • Eliminated database I/O bottlenecks by implementing distributed Redis caching layer increasing API throughput by 30% for 500 concurrent users
    • Integrated CI/CD workflows for automated model deployment reducing release cycle time from weeks to under 3 months
  • Advanced Application Engineering Analyst
    2023-06 - 2023-08
    Accenture
    Engineered automated threat detection and SOAR playbooks for enterprise security monitoring.
    • Engineered automated threat detection logic in Azure Sentinel using KQL processing 10 million daily log events
    • Designed Python-based SOAR playbooks to automate incident response reducing Mean Time to Respond (MTTR) by 80%
    • Mapped detection rules to MITRE ATT&CK framework achieving 89% classification accuracy
    • Hardened application perimeters by identifying and patching 15 critical vulnerabilities including SQL injection and XSS vectors
  • Web Developer
    2022-05 - 2022-07
    Indian Red Cross Society
    Delivered Drupal-based CMS to digitize volunteer registry.
    • Delivered Drupal-based CMS to digitize volunteer registry reducing manual data entry efforts by 50% for 10k monthly visitors

Skills

Programming

  • Python
  • R
  • Java
  • C
  • JavaScript
  • TypeScript
  • HTML/CSS
  • Bash/Shell

Data & Databases

  • SQL
  • MySQL
  • PostgreSQL
  • MongoDB
  • Cassandra
  • Snowflake
  • Neo4j
  • Pinecone
  • Apache Spark
  • Kafka

AI/ML

  • PyTorch
  • TensorFlow
  • Keras
  • Hugging Face
  • LangChain
  • LlamaIndex
  • LangGraph
  • PySpark
  • NLTK
  • SpaCy
  • Scikit-Learn

DevOps & Cloud

  • Git
  • Docker
  • Kubernetes
  • Jenkins
  • CI/CD
  • REST APIs
  • AWS
  • Azure
  • GCP
  • Terraform
  • Ansible

Core Competencies

  • LLMs
  • Generative AI
  • RLHF/DPO
  • Deep Learning
  • NLP
  • Computer Vision
  • Survey Methodology
  • Causal Inference
  • MLOps

Publications

  • Causal Inference Methods in Educational Research
    2024
    Journal of Educational Measurement
    A comprehensive review of causal inference methods applicable to educational data, including propensity score methods, instrumental variables, and regression discontinuity designs.

Presentations

  • Advances in Causal Inference for Educational Research
    2024
    American Educational Research Association (AERA) Annual Meeting
    Philadelphia, PA, USA
    Presented novel methods for causal inference in educational settings with complex data structures.

Teaching

  • Data Privacy and Survey Methodology
    2025
    Joint Program in Survey Methodology (JPSM), University of Maryland
    Role: Teaching and Graduate Assistant
    Translated complex data privacy frameworks into actionable learning modules for 23 graduate students; reengineered Canvas LMS infrastructure with automation scripts reducing course setup time by 40%.

Portfolio

  • Weather Guardian: Automated Daily Weather Briefing System
    2024
    Automation
    Built an intelligent workflow using n8n, OpenWeatherMap API, and Supabase to automatically generate and email daily weather briefings.
  • Trademark Search Engine
    2024
    Ml
    Production-grade trademark search engine processing 2.4 million images using FastAPI, Faiss vector embeddings, and HNSW indexing.

Languages

  • English
    Professional working proficiency
  • Hindi
    Native speaker

Interests

  • Machine Learning & AI
    RAG Architectures, Generative AI, LLMs, MLOps
  • Data Engineering
    ETL Pipelines, Geospatial Analytics, Data Quality, Scalable Systems
  • Survey Data Science
    Survey Methodology, Causal Inference, Missing Data, Longitudinal Analysis