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masoodahmedah

Masood A

@masoodahmedah

Data Scientist AIML Engineer

Indien
Urdu, Hindi, Englisch, Kannada
Einige Informationen werden in englischer Sprache angezeigt.
Über mich
I am a Data Scientist and AI/ML Engineer specializing in building and deploying production ML and GenAI systems. I have extensive experience in time-series forecasting, predictive maintenance, and RAG pipelines using Python, TensorFlow, and FastAPI. I focus on delivering live cloud applications that solve real-world business problems.... Mehr lesen

Kompetenzen

m
masoodahmedah
Masood A
offline • 
Durchschnittliche Antwortzeit: 1 Stunde

Meine Dienstleistungen

Maschinelles Lernen
I will build machine learning and predictive models
Ab100 $ / ProjektWeitere Details

Arbeitserfahrung

freelance

Freelance Data Scientist & Web Developer

freelance • Freiberufler

Aug 2023 - Present • 3 yrs 2 mos

Delivered websites and data projects for 5 clients, mainly restaurants and small retail shops. Built fast, mobile-first business websites with React, TypeScript, Tailwind CSS and HTML/CSS. Added local SEO and smooth scroll animations. Built Python machine-learning solutions for client data problems and managed each project end to end.

Intellipaat

Data Scientist Intern

Intellipaat

Nov 2024 - Nov 2025 • 1 yr

Built a Census Income classifier with 87% accuracy and 0.92 ROC-AUC on 48K records. Forecast 12 weeks of Walmart sales with Holt-Winters and found an 8% holiday uplift. Cleaned and engineered features for classification, regression, clustering and forecasting models in Python and SQL. Turned model results into visual reports for non-technical stakeholders.

University_of Greenwich

Graduate Research Project - Stochastic Diffusion Search for Feature Selection

University of Greenwich

Apr 2024 - Dec 2024 • 8 mos

Pioneered application of Stochastic Diffusion Search (SDS) algorithm for feature selection optimization across diverse high-dimensional datasets. Achieved 5-15% accuracy improvements while reducing feature dimensions by 80-95%. Implemented and compared multiple ML algorithms: Random Forest, Logistic Regression, SVM, XGBoost.