Nisarga S M

My career narrative has evolved over time, and I know it will continue to do so. I started out as a Computer Science Engineer, deeply focused on technical foundations. But over time, I found myself asking bigger questions: What kind of work energizes me? Where can I make the most meaningful impact? Those early years were filled with both learning and uncertainty. I enjoyed coding, but what really drew me in was the why behind the data — the patterns, the insights, the decisions it could influence. That curiosity led me to pivot into data analytics, a space where logic, creativity, and business value intersect. Since then, I’ve worked on diverse projects — from pension fund performance tracking to building real-time sentiment analysis systems. I’ve developed dashboards, automated reporting workflows, trained machine learning models, and translated technical findings into actionable insights for non-technical stakeholders. Most recently, I completed my Master’s in Data Analytics at Dublin Business School, where my research focused on NLP and real-time sentiment classification. I designed a Retrieval-Augmented Generation (RAG) model using GPT-4 and ChromaDB to enhance the quality of customer feedback interpretation in e-commerce settings — blending AI with practical business intelligence. While I’m proficient in tools like SQL, Python, Power BI, Tableau, AWS, and Azure, what drives me is more than just the stack. It’s about solving real-world problems, making data approachable, and helping organizations move from confusion to clarity. Want a data analyst who doesn’t just interpret numbers but sparks innovation through powerful, data-driven storytelling? Let’s connect.

Data Analyst with 3 years of experience in BI, SQL, Python, and ETL automation. Skilled in building dashboards, improving data quality, and delivering insights for decision-making across finance, telecom, and customer analytics.

M.Sc. in Data Analytics (1:1) from Dublin Business School, focused on predictive analytics, data engineering, and visualization. Completed industry-oriented projects, including real-time sentiment analysis and clinical data modeling.