Neha Kulhade

Designed production-grade Generative AI workflows using LLMs with advanced prompt engineering and evaluation strategies to improve response quality and domain relevance. Built scalable RAG systems with automated embeddings and vector databases, enabling enterprise-level semantic search and knowledge-grounded generation. Integrated end-to-end ML/GenAI pipelines from data ingestion to deployment, ensuring model monitoring, versioning, and maintainability under SDLC and Agile practices.

Developed machine learning and NLP models for multiple freelance clients, focusing on predictive analytics, recommendation systems, and sentiment analysis. Designed and deployed end-to-end AI solutions, optimizing performance using hyperparameter tuning and model ensembling. Wrote technical blogs and articles on AI, ML, and NLP, increasing engagement and knowledge sharing within the data science community.

Built NLP pipelines using deep learning models like LSTM, BERT, and RoBERTa for political bias and ideology classification, incorporating keyword-aware classifiers and SMOTE to boost minority class performance by 28%. Developed and optimized a Retrieval-Augmented Generation (RAG) system using Ollama, LangChain, and Llama3, integrating scalable retrieval through automated embeddings with nomic-embed-text. Scraped and structured large-scale Indian news data into a macro database, enabling efficient retrieval and powering classification and generative tasks.

Developed predictive models for student churn analysis using Logistic Regression, XGBoost, and Random Forest, reducing churn by 15% through improved early intervention strategies. Performed data cleaning, EDA, and feature engineering, and visualized key churn drivers through interactive dashboards and reports. Designed GPT-4 and Jasper-based prompt workflows to enhance student support and productivity, delivering documentation and demo templates for seamless platform integration.

Collaborated with a team to analyze and visualize data, leveraging critical thinking, collaboration, and communication skills. Implemented statistical analysis to draw insights from structured and unstructured datasets. Created insightful data dashboards and reports for business decision-making using Tableau and Power BI.

Managed social media accounts and designed daily graphics to maintain a consistent and engaging online presence across platforms. Optimised content performance by analysing user engagement metrics through Google Analytics, social media insights, A/B testing, and interactive Power BI dashboards tracking campaign effectiveness and trends.

Monitored and analysed campaign performance, customer interactions, and sales trends using data tools like Excel, SQL, and Power BI to support targeted lead generation and optimise sales efforts. Conducted in-depth market research on customer demographics, buying behaviour, and competitor activity, enabling the development of data-driven marketing strategies and impactful performance dashboards.

Analysed trainee progress data to optimise training programs and improve learning outcomes. Utilised Excel & SQL to track attendance, assessment scores, and training effectiveness.