Nitika Arya

I’m currently an Analyst – AI/LLM, where I annotate and validate large-scale datasets to support training and evaluation of AI/LLM models. I focus on data quality checks and consistency validation across structured and unstructured data, then analyze model outputs and edge cases to improve annotation accuracy and dataset reliability.

Previously, as a Trainee Decision Scientist at Mu Sigma Business Solutions Ltd., I translated business requirements into structured data and reporting solutions. I processed and validated datasets with SQL, Excel, and Python for KPI tracking and analysis, and I built Power BI dashboards to support business decision-making in Agile teams using JIRA and Confluence.

I combine strong analytics fundamentals with AI exposure. On the technical side, I work across SQL (joins, aggregations), Python (Pandas, NumPy), advanced Excel, and exploratory data analysis, and I’ve applied core ML concepts like regression, classification, feature engineering, model evaluation, and data preprocessing. For LLM workflows, I’ve explored LLMs, Retrieval-Augmented Generation (RAG), and LangChain concepts, including prompt engineering and agentic AI-style reasoning.

I also build practical tools that turn analysis into action—like an AI-powered analytical assistant prototype that summarizes trends and anomalies, and dashboards and pipelines that automate recurring data tasks. I’ve demonstrated impact through a published research paper (Crop Disease Identification using Deep Learning Techniques), an AI hackathon win (Tourist Recommender System), and certifications like Microsoft Power BI Data Analyst (PL-300), and I bring a collaborative, detail-obsessed approach to every dataset and dashboard.