Nishith Thakkar

IEEE-published researcher and Data Analyst with hands-on experience across data science, artificial intelligence, machine learning, and advanced analytics, spanning industries including EdTech, FinTech, and enterprise AI. Currently contributing to the 2026 Human Skills Report at LEVRA, applying regression, clustering, predictive modelling, and statistical analysis to three years of learner data to identify trends, patterns, and actionable insights.

Previously worked as a Prompt Engineer on Alphabet’s Arcade and Meta’s SRT platforms, evaluating and fine-tuning Large Language Models (LLMs) for multimodal reasoning, factual accuracy, instruction following, and cultural alignment. Experienced in building data-driven solutions using Python, SQL, PySpark, Databricks, Apache Spark, AWS (S3, QuickSight, IAM), Tableau, Scikit-learn, and TensorFlow, with practical exposure to data pipelines, cloud platforms, ETL processes, and business intelligence.

Published research in IEEE on deep learning and CNN-based medical image classification for brain tumour detection, demonstrating experience in research methodology, model development, evaluation, and technical communication. Built end-to-end machine learning pipelines processing 2M+ records for credit-risk analytics, incorporating data preprocessing, feature engineering, predictive modelling, model evaluation, and analytical reporting. Also designed interactive BI dashboards and data visualisations to translate complex datasets into clear insights that support business decision-making.

Strong interest in Data Science, Machine Learning, AI, and Analytics, with a focus on transforming complex data into scalable, reliable, and business-focused solutions. MSc in Business and Data Analytics from Ravensbourne University London and BSc in Information Technology from LJ University.