Akhtar ali

Aspiring Data Scientist · ML Engineer

Noida, Uttar Pradesh, India

@akhtar_ali

LinkedIn GitHub

0 followers

About

Aspiring Data Scientist and ML Engineer with strong expertise in Python, SQL, and modern AI technologies. Experienced in data analysis across healthcare and e-commerce domains, with hands-on work in LLMs, NLP, computer vision, and machine learning.

Experience

Data Science Trainee

Jan 2024 – Present

Education

B.Tech in Computer Science Engineering

Shri Ramswaroop Memorial University

Computer Science Engineering · 2022 – 2026

Skills

<3 months

SQL RAG NLTK Bert NumPy Keras Spacy Python Pandas OpenCV Plotly FastAPI PyTorch Seaborn Streamlit LangChain JavaScript Matplotlib TensorFlow Embeddings Gemini APIs scikit-learn Tokenization Classification Transfer Learning Prompt Engineering Sentiment Analysis Image Classification CNN (Convolutional Neural Network)

Tools / apps / platforms

<3 months

Git MySQL GitHub MongoDB Tableau VS Code PostgreSQL Jupyter Notebook Microsoft Power BI Hugging Face Transformers

Languages

Not stated

Hindi Speak English Speak

Projects

Customer Segmentation using ML

Python, Scikit-learn, Pandas

Segmented 5,000+ customers using K-Means clustering and identified 4 distinct customer segments with tailored retention strategies. Projected 20% churn reduction through targeted interventions.
Sales & Customer Analytics

Python, SQL, ML, Power BI

Processed 50,000+ sales transactions using SQL and Python. Applied RFM analysis and K-Means clustering on 8,500+ customers to identify revenue opportunities through analytics insights.
Healthcare Data Analysis

Python, Power BI, SQL

Analyzed 25,000+ patient records with 99.5% accuracy. Built Power BI dashboards tracking KPIs such as recovery rate and occupancy, and automated reporting processes saving 20+ hours per month.
Sentiment Analysis on Product Reviews

Python, NLTK, Transformers

Analyzed 10,000+ product reviews using BERT-based models for sentiment classification. Achieved 88% accuracy using fine-tuned DistilBERT and visualized sentiment trends using Plotly and Tableau.
LLM-Powered Document Q&A System (RAG)

LangChain, Hugging Face, FAISS

Built a document-based question-answering system using LangChain and RAG architecture. Used Hugging Face embeddings and FAISS for vector similarity search, enabling querying on PDF documents with context-aware responses.

Courses & certifications

Power BI Associate · Microsoft
Statistics for Data Science · LinkedIn Learning
Hugging Face NLP Course · Hugging Face
LangChain for LLM Application Development · DeepLearning.AI
TCS iON Data Analytics Certification · TCS iON
HackerRank SQL Advanced Certification (5-Star, Top 3%) · HackerRank
IBM Data Analytics with Python · IBM
IBM Data Science & Artificial Intelligence Certification · IBM

🏆 Achievements & awards

Analyzed 75,000+ records across healthcare, e-commerce, and NLP projects

Recognized in the resume's key achievements section.
Built 10+ dashboards and 8+ ML/DL models

Included CNNs and NLP models among the projects.
Implemented RAG-based Q&A system and sentiment analysis using Transformers

Highlighted as a key achievement.
Reduced reporting time by 40-70% through automation

Reported impact from automation work.

🎯 Hobbies & interests

LLMs
Generative AI
NLP
MLOps
Data Science

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