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