Data Analyst Machine Learning

Nancy Gahlot

+91-701******* ***************@*****.*** LinkedIn GitHub

Technical Skills

Languages: Python, SQL

Data Tools: Power BI, Excel, BigQuery, Metabase, Google Sheets Libraries/Frameworks: pandas, NumPy, scikit-learn, TensorFlow, Matplotlib GenAI & NLP: LLMs (GPT), LangChain, Hugging Face, RAG, Prompt Engineering, NLP Other Tools: Git, Selenium

Core Concepts: Machine Learning, Deep Learning, Agentic AI, Embeddings, Statistics, DSA Experience

Data Analyst August 2023 – August 2025

Coding Ninjas

• Led the development of a Generative AI-based notes tool using RAG and LLMs, reducing manual effort by 40% and saving 30+ hours/month.

• Built an AI-powered MCQ explanation engine using NLP pipelines, reducing TA content creation costs by 8L+ annually.

• Analyzed 10k+ learner chat records and feedback using SQL, identifying 15+ curriculum gaps; 80% resolved within 3 months.

• Discovered that 64% of refund cases came from professionals, enabling targeted UX changes that reduced refund rates by 12%.

• Developed leadership dashboards that improved visibility into student metrics and boosted outreach conversion by 25%.

Data Analyst Intern February 2023 – August 2023

Coding Ninjas

• Designed and automated 20+ dashboards in Metabase and Google Sheets for campaign tracking, reducing report generation time by 60%.

• Saved 10+ hours/week through Python-based automation of repetitive analytics tasks.

• Analyzed user behavior from 15,000+ learners, generating a 10% revenue uplift via course bundling strategy.

• Built a predictive model to segment learners by engagement level, increasing course completion from 58% to 90%. Projects

NPS Attribution Model Python, MySQL, Machine Learning

• Built a predictive model to estimate Net Promoter Score (NPS) within the first month of a learner’s course.

• Performed data wrangling and feature engineering using MySQL and Python; trained supervised learning models for NPS forecasting.

• Enabled early intervention strategies, which helped improve user satisfaction and reduce churn. Pneumonia Detection Using X-rays Python, Deep Learning

• Trained CNN models (ResNet, VGG16, DenseNet201) on labeled chest X-ray datasets for multi-class classification

(bacterial, viral, normal).

• Applied advanced pre-processing and fine-tuning; optimized model performance using accuracy, recall, and F1-score.

• Demonstrated real-world application of deep learning in medical image classification. Education

Punjab Engineering College, Chandigarh Aug 2021 – Jun 2023 M.Tech in Computer Science CGPA: 7.81

Deenbandhu Chhotu Ram University of Science and Technology Aug 2017 – Jul 2021 B.Tech in Computer Science CGPA: 8.0

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