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Data Scientist @ Quant | MSc Data Science
Experience Data & AI professional, have developed and deployed all kinds of analytical models, from predictive and forecasting models, recommendation engines, computer vision models, and LLM systems. Strong at leading projects across diverse data sources, resolving ambiguity, and identifying the data that matters, with hands-on experience using databases, APIs, web scraping, and IoT streams. Designs and implements end-to-end data and ML pipelines tailored to project requirements and scalability, coding every stage from data ingestion and analysis to model development and automated deployment across on-prem, cloud, and edge environments. Owns the end-to-end analytics pipeline from raw data to executive-ready dashboards, translating complex results into clear, actionable insights that drive decisions and measurable outcomes.
University of Malaya
Master of Data Science, Data Science
January 1, 2020 – January 1, 2022
Islamic University of Madinah
Bachelor of Electrical engineering, Electrical and Electronics Engineering
January 1, 2014 – January 1, 2018
Quant
Data Scientist
September 1, 2024 – Present
Riyadh, Saudi Arabia · On-site
Saal.ai
AI Engineer
July 1, 2023 – September 1, 2024
United Arab Emirates · On-site
Maxis
Data Scientist
March 1, 2022 – October 1, 2022
WP. Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia · Hybrid
MALAYSIA-JAPAN INTERNATIONAL INSTITUTE OF TECHNOLOGY (MJIIT)
IoT Engineer
June 1, 2017 – September 1, 2017
WP. Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia
COVID-19 Clinical Trial Studies Analysis - Descriptive Analysis & Dashboard
January 1, 2021 – April 1, 2021
I have worked and managed a team to Analyze worldwide clinical trial studies data about COVID-19 and to develop Dashboard Tools used: |R language - ggplot2 - dplyr - tidyr - Leaflet - Shiny| GitHub link: github.com/yousif4111/PDS_Clinicaltrials_COVID_19 The Dashboard is publicly available in link: yousifabd.shinyapps.io/PDS_Clinicaltrials_COVID_19/
AWS Certified Machine Learning – Specialty
Amazon Web Services (AWS)
June 25, 2026 – Present
AWS Certified Cloud Practitioner
Amazon Web Services (AWS)
June 25, 2026 – Present
Graph Data Modeling Fundamentals
Neo4j
June 25, 2026 – Present
Git and GitHub
IBM
June 25, 2026 – Present
Specialized Models: Time Series and Survival Analysis
IBM
June 25, 2026 – Present
Supervised Machine Learning: Regression
IBM
June 25, 2026 – Present
Exploratory Data Analysis for Machine Learning
Coursera
June 25, 2026 – Present
Cultural Fit Analysis
The candidate has worked in various domains (PropTech, finance, sports, border security) and on diverse ML problems (geospatial AI, time series, NLP, fraud detection), indicating adaptability and a broad interest in applying ML. The experience in both startup (Saal.ai) and established company (Quant) environments suggests flexibility. The personal project on COVID-19 data analysis also shows initiative and a drive for continuous learning. The target role of ML Engineer aligns well with the candidate's recent experience and stated core skills.
Soft Skills & Operational Fit
The candidate's project descriptions indicate experience in leading teams and delivering solutions for diverse clients, suggesting good project management and client-facing skills. The MLOps experience implies an understanding of operationalizing ML models. However, without specific psychometric or English test results, a detailed assessment of communication, logical reasoning, work attitude, stress handling, and team collaboration is not possible.