Data Scientist - ML, LLMs, and Revenue Optimization Specialist

Umeaiman Merchant

+1-813-***-**** *************@***.*** LinkedIn Profile Portfolio GitHub Profile SUMMARY

• Data Scientist with 4+ years of experience designing end-to-end AI solutions using Python, LangChain, MLflow, and AWS.

• Skilled in LLM orchestration, data pipelines, and predictive analytics to drive revenue optimization and customer engagement.

• Passionate about leveraging ML and LLM to end-to-end model development, from data engineering to deployment and storytelling. EDUCATION

Masters in Science, Artificial Intelligence and Business Analytics (GPA:3.95) University of South Florida, Tampa, FL Aug 2024-May 2026 Bachelor in Technology, Electronics Engineering (GPA:8.6) Vishwakarma Institute of Technology, Pune, MH Aug 2017-June 2021 CORE SKILLS

Programming Languages: Python, R, JavaScript, C#, C++ Web & UI: React, HTML, CSS, FastAPI, Streamlit, Flask Data Science Library: NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow, PySpark, MLOps, MLflow GenAI & LLMs: LangChain, LlamaIndex, Prompt Engineering, RAG, Snowflake, AWS SageMaker, AWS Redshift NLP & AI Models: SpaCy, LightGBM, OpenAI, Gemini, LLaMA, GPT-4 AI Technology: Supervised & Unsupervised Learning, NLP, AI Agents ML Models: Bayesian Networks, Regression Analysis, SVMs, Random Forests, XGBoost Analysis: Data Wrangling & Cleaning, Feature Engineering, EDA, A/B Testing (Hypothesis Testing) Visualization: Matplotlib, Seaborn, Plotly, Tableau, Power BI, Data Storytelling Tools & Platforms: Git, GitHub, GitLab, Bitbucket, Docker, Jupyter Notebooks, VS Code, PyCharm, Kubernetes, Azure, CI/CD Databases: MySQL Workbench, Microsoft SQL Server (SQL), MongoDB (NoSQL), PostgreSQL, Spark PROFESSIONAL EXPERIENCE

Data Science Intern Orlando, FL

Universal Destinations and Experiences Sept 2025-Present

• Revenue Management: Designed and implemented a ML model using Python, Databricks and Machine learning algorithms with supervised fine-tuning to optimize product decisions, with increase in revenue and customer satisfaction.

• Delivered data ingestion pipelines, enabling real-time data updates and reducing manual effort by 40%.

• Created executive-level presentations and visual analytics, leveraging Snowflake to communicate revenue insights and model results, enabling data-driven decision-making across leadership teams. Data Science Project Lead Intern Jacksonville, FL

FL-DSSG (University of North Florida) May 2025-Aug 2025

• School-Level Recognition: Designed a clustering ML model, and MLflow based school ranking system leveraging extended scoring rubrics across funding, governance, engagement, and quality dimensions to identify top 10 arts-focused schools.

• Implemented a GenAI feedback engine implementing LLMs to automatically generate personalized principal reports, improving award decision-making while ensuring strong data security and privacy in alignment with privacy-preserving AI principles. Technology Consultant Mumbai, MH

EY LLP Oct 2023-Jul 2024

• AI Chatbot: Designed and deployed a GenAI-powered Retrieval-Augmented Generation (RAG) chatbot using LangChain, Python, FastAPI, and AWS (Lambda, S3), boosting user engagement by 35%.

• Built vector-based semantic search pipelines with FAISS and OpenAI embeddings, improving contextual accuracy and minimizing hallucination errors in enterprise knowledge retrieval.

• Cross-functional collaboration to define architecture, automate CI/CD with GitHub Actions, and containerize deployments using Docker for version control.

Senior Software Engineer Pune, MH

LTIMindtree Limited Jul 2021-Oct 2023

• Data Quality: Engineered ELT (Extract, Load, Transform) processes and Statistical Analysis adopting Oracle SQL, contributing to a 20% reduction in data-related issues by ensuring efficient data flow and integrity.

• Coordinated with cross-functional teams to implemented Tableau dashboards for anomaly detection and used SQL and RPA

(UiPath) for advanced data manipulation, leading to a 25% reduction in post-implementation defects. PROJECT EXPERIENCE

Research Project: GUI vs. CUI Exploring Conversational AI in Academia May 2025-Jul 2025

• Engineered and evaluated an AI agent chatbot using LangChain, OpenAI embeddings, Docker, Streamlit, a vector database, and PostgreSQL to analyze how GUI and CUI designs impact user experience, uncovering key usability trade-offs. Research Project: Sepsis Mortality Analysis Aug 2024-May 2025

• Built a predictive machine learning model utilizing demographic, procedural, and comorbidity data to forecast sepsis mortality within 7 days of hospitalization, achieving F1-score of 0.74. InterVista.ai: AI based Mock Interview Website Mar 2024-Aug 2024

• Envisaged and deployed AI chatbot based mock interview platform with Audio capabilities leveraging Python, dataset annotation, fine tune AI ethics, and prompt engineering large language models (LLM) increasing participant confidence by 50%.

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