Creating a Pathway to a Data Science and Data Engineering Career
Project-based courses and a role as a teaching assistant helped Neha Devarapalli, MS’25, information systems, enhance her technology background and boost her confidence to seek a career at the intersection of data science and data engineering.
Neha Devarapalli, MS’25, information systems, earned an undergraduate degree in computer science engineering at Jawaharlal Nehru Technological University in Hyderabad, India, where she built a strong foundation in programming and data science. She completed projects ranging from an emergency SOS application to a deep learning-based sign language detection system.
When she decided to pursue an advanced degree, Devarapalli’s selected Northeastern because of its emphasis on experiential learning, cutting-edge research, and strong curriculum. She credits the program’s flexibility and elective courses focused on artificial intelligence, cloud computing, and data analytics as major factors in her decision.
Courses such as Program Structure and Algorithms gave Devarapalli a strong theoretical foundation, while hands-on, project-based courses like Big Data Systems & Intelligence Analytics allowed her to work on end-to-end data pipeline architecture, real-world AI integrations, and multi-agent systems. The balance between rigorous fundamentals and modern, application-driven learning helped her build both the depth and breadth she wanted to achieve her career goals.
Devarapalli credits Robin Hillyard, associate teaching professor, with transforming her understanding of data structures and algorithms. She believes that Hillyard’s methodical approach and clear delivery helped her reach a level of mastery that later enabled her to serve as a teaching assistant in this course.
She says Sri Krishnamurthy, adjunct faculty member, who taught Big Data Systems & Intelligence Analytics, helped her bridge the gap between academic learning and real-world applications. His focus on data pipelines, Snowflake, LangGraph, RAG architecture, and multi-agent systems sparked her enthusiasm for building intelligent, data-driven applications and significantly shaped the projects she pursued.
For her final project in Krishnamurthy’s course, Devarapalli and her team developed InterviewGraph, an ambitious and innovative platform that reimagines the entire interview preparation experience. Together with her team, she built a system that integrates advanced Retrieval-Augmented Generation (RAG) workflows, multi-agent orchestration with LangGraph, structured knowledge retrieval from Snowflake, and real-time unstructured content collection through web scraping and intelligent search agents.
The platform offers personalized study guides based on a user’s resume and job description; realistic mock interview simulations via a speech interface powered by ElevenLabs; and dynamic feedback after mock sessions to pinpoint strengths and areas for improvement.
One of the most significant challenges in the project was ensuring the relevance and realism of the mock interviews. Large Language Models (LLMs) can produce incorrect responses, often referred to as hallucinations, particularly when generating technical or behavioral questions. To combat this, Devarapalli employed prompt engineering, hybrid grounding using Snowflake and RAG context, and implemented validation layers that assessed content quality before delivering it to users. The most effective strategy proved to be early modular design, layered validation at each node, and rigorous internal testing prior to full integration. InterviewGraph has potential as a career acceleration tool, with possible applications in university career services and recruiting agencies.
Her time as a teaching assistant in the Program Structure and Algorithms course ignited a passion for mentoring. Her dedication was recognized when she received the 2025 COE Outstanding Student Teaching, Service, and Leadership Award and the MGEN Teaching Assistant Award. These honors affirmed her love for teaching, leadership, and giving back to the tech community.
Looking ahead, she aspires to work at the intersection of data science and data engineering, building intelligent systems that are both technically robust and socially impactful.
“Northeastern gave me the confidence to tackle ambitious ideas, lead with purpose, and embrace lifelong learning,” says Devarapalli. “I will always be grateful for the environment it created. It challenged me and equipped me with the tools I’ll need to rise to future challenges.”