---
title: "Rahul Yadav - Data Science Trainee in Dubai | Tal"
description: "Meet Rahul Yadav, Data & AI Professional | Python, SQL, Power BI, ML, NLP | Data Analyst • Business Analyst • Data Scientist • AI/ML Engineer based in Dubai. AI stack includes claude code, kimi, and openai. Explore public work links including github."
image: "https://tal.club/meet/rahul-yadav-9/share-image"
---

# Rahul Yadav on Tal

## Headline

Data & AI Professional \| Python, SQL, Power BI, ML, NLP \| Data Analyst • Business Analyst • Data Scientist • AI/ML Engineer

## About

Data Analyst \| AI/ML Engineer \| Data Scientist \| BI/NLP Specialist \| B\.Tech CSE \| Internshala DSPG \| AI/ML Intern Results\-driven and analytically minded professional with hands\-on experience across 10\+ real\-world data projects in machine learning, AI, data analytics, NLP, and business intelligence\. A B\.Tech CSE graduate from JECRC University, I completed a 6\-month Data Science Placement Guarantee Program by Internshala and a 4\-month internship as an AI/ML Programmer at InternPe, where I built and deployed impactful, data\-driven solutions\. Skilled in translating raw data into strategic insights, building end\-to\-end ML pipelines, and deploying scalable solutions using Python, SQL, Power BI, and Streamlit\. Adept at problem\-solving, cross\-functional collaboration, and delivering outcomes aligned with business goals\. Core Competencies: • Data Analytics & BI: Excel, Power BI, Tableau, KPI dashboards, data storytelling • Programming & ML: Python, Scikit\-learn, XGBoost, Pandas, NumPy, TensorFlow, Keras • Databases & SQL: Advanced SQL \(CTEs, window functions, joins\), data cleaning, ETL • NLP & Deep Learning: TF\-IDF, NLTK, text classification, sentiment analysis, ANN/CNN • Deployment: Streamlit, Flask, Git/GitHub • Soft Skills: Critical thinking, attention to detail, adaptability, communication Key Projects: • Customer Churn Prediction: Trained an XGBoost model to predict churn with high precision, supporting retention strategies\. • Airbnb Price Estimator: Used Random Forest and feature engineering to estimate prices for 1,000\+ listings\. • IMDb Sentiment Analysis \(NLP\): Deployed TF\-IDF \+ logistic regression to classify 50,000\+ reviews with \\\~89% accuracy\. • News Category Classifier \(NLP\): Used NLTK & text vectorization to classify articles across business, politics, and sports\. • Walmart Sales BI Dashboard: Designed a Power BI dashboard analyzing regional underperformance, seasonality & revenue KPIs\. • Rainfall Forecasting App \(ANN\): Built a city\-wise rainfall prediction model using artificial neural networks & deployed via Streamlit\. • E\-commerce & Robotics Projects: Created a full\-stack shopping platform, AI\-based line follower & obstacle avoider robots, and IoT\-driven smart home systems\. Actively seeking opportunities in Data Science, Machine Learning, AI/NLP, or Business Intelligence, where I can contribute to innovation, automation, and data\-driven decision\-making\. Let’s connect and collaborate to solve real\-world problems using the power of data\!

## Location

Dubai

## AI stack

claude code

kimi

openai

ChatGPT

## Work experience

Data Science Trainee at Internshala Trainings, Oct 2024 \- Mar 2025 · 6 mos, Remote, Successfully, completed a 6\-month, immersive, industry\-aligned training simulating a full\-time data science internship\. Gained hands\-on experience in data analysis, machine learning, NLP, deep learning, and BI tools, with an emphasis on real\-world applications\. Worked on multiple capstone\-level projects using real datasets to develop complete ML pipelines, dashboards, and NLP models, showcasing practical problem\-solving and analytical skills\. Core Responsibilities & Skills Acquired: \* Developed 9\+ real\-world data science projects across domains like marketing, e\-commerce, finance, and NLP\. \* Built ML models using Scikit\-learn, XGBoost, and Pandas for regression, classification, and clustering\. \* Performed advanced data cleaning, EDA, and visualization using NumPy, Matplotlib, and Seaborn\. \* Designed dashboards and business reports using Power BI and Excel to extract actionable insights\. \* Built full\-fledged NLP pipelines for text classification, sentiment analysis, and keyword extraction\. \* Implemented end\-to\-end ML workflows including data preprocessing, model training, tuning, and evaluation\. Highlighted Projects: \* Customer Churn Prediction: Developed an XGBoost model to predict telecom customer churn, improving business retention insights\. \* Airbnb Price Estimation: Built a regression model using Random Forest to predict listing prices with high accuracy\. \* IMDb Sentiment Analysis: Created an NLP pipeline to classify movie reviews as positive/negative using TF\-IDF and logistic regression\. \* News Article Classification: Classified news articles into categories like politics, sports, business, etc\., using NLP and text vectorization\. \* Walmart Sales Performance: Used SQL to analyze sales trends, and identify low\-performing areas\. \* KPMG data analysis: Applied Excel\-based analytics to interpret customer demographics and transactions\. \* Electric Vehicle Market Study: Evaluated EV growth, delivering future predictions and regional trends\.i

AI/ML Programming at InternPe, Mar 2024 \- Jul 2024 · 5 mos, Jaipur, Rajasthan, India, During my internship at Internpe, I had the opportunity to work on various innovative projects and hone my skills in Artificial Intelligence \(AI\) and Machine Learning \(ML\)\. This experience provided me with a comprehensive understanding of the AI/ML lifecycle, from data collection and preprocessing to model deployment and performance monitoring\. Key Responsibilities: 1\)\. Project Development: Collaborated with a team of skilled professionals to design and implement AI/ML models, focusing on real\-world applications and problem\-solving\. 2\)\. Data Analysis & Preprocessing: Engaged in extensive data analysis using Python, Pandas, and NumPy, ensuring the accuracy and reliability of datasets through rigorous preprocessing techniques\. 3\)\. Model Training & Evaluation: Developed and trained various machine learning models, including regression, classification, and clustering algorithms\. Employed libraries such as TensorFlow, Keras, and Scikit\-learn to optimize model performance\. 4\)\. Algorithm Implementation: Worked on implementing advanced machine learning algorithms, including Artificial Neural Networks \(ANN\) and Density\-Based Spatial Clustering of Applications with Noise \(DBSCAN\), to tackle complex problems\. 5\)\. Interactive Applications: Created interactive web applications using Streamlit, enabling real\-time user interaction and data visualization for enhanced user experience and decision\-making\. 6\)\. Performance Monitoring: Utilized metrics and visualization tools to monitor model performance and accuracy, ensuring continuous improvement and scalability of solutions\. 7\)\. Collaborative Environment: Actively participated in team meetings, brainstorming sessions, and code reviews, fostering a collaborative and innovative work environment\. This internship was instrumental in advancing my expertise in AI/ML, enhancing my problem\-solving abilities, and preparing me for future challenges in the field\.

## Education

Data Science Placement Guarantee Course, Data Science, Internshala Trainings

Bachelor of Technology \- BTech, Computer Science and Engineering, JECRC University

## Public links

- github: https://github\.com/War\-Human

[View the original profile](https://tal.club/meet/rahul-yadav-9)

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