Md. Al Mamun

Data Science

https://www.opentalent.in/md-al-mamun

Key Strengths

Strong academic background in Computer Science and Engineering with a focus on Data Science and Machine Learning.
Demonstrated experience in various academic projects related to deep learning, machine learning for prediction, and recommendation systems.
Multiple publications in relevant fields, indicating research capability and contribution to the domain.
Proficiency in Python, SQL, Git, and GitHub, essential tools for data science.
Experience with data processing techniques (handling missing values, encoding, normalization) and NLP techniques (tokenization, stopword removal).

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

About

I am deeply passionate about data science and analysis, with a focus on leveraging technology to extract meaningful insights from complex datasets. I have gained hands-on experience through various projects, including feature assembly and accuracy comparison, cyberbullying detection, natural language processing, image processing, and comparing machine learning algorithm accuracies. These experiences have honed my skills in problem-solving, critical thinking, and innovation, driving my commitment to advancing data-driven solutions.

Top Skills

Machine LearningPythonSentiment Analysis

Education

Daffodil International University

Bachelor of Science · Computer Science and Engineering

August 1, 2020 – June 30, 2024

Savar Model College

Higher Secondary Certificate (HSC)

June 1, 2019 – May 31, 2019

Gakulnagar High School

Secondary School Certificate (SSC)

June 1, 2017 – May 31, 2017

Experience

Daffodil International University

Research Assistant

March 1, 2024 – June 1, 2025

Dhaka, Dhaka Division, Bangladesh

Projects

Fruits Detection using Deep Learning Algorithms

June 1, 2026 – Present

Implemented deep learning techniques for detecting and classifying various fruits in images.

View Project

Cervical Cancer Prediction using ML

June 1, 2026 – Present

Developed a cervical cancer prediction model utilizing machine learning techniques.

View Project

Movie Recommendation System

June 1, 2026 – Present

Engineered a recommendation system using collaborative filtering.

View Project

Certifications

A comprehensive Malabar Spinach dataset for diseases classification

ScienceDirect

June 1, 2026 – Present

Certificate of Completion: Become a Machine Learning Engineer

LinkedIn Learning

June 1, 2026 – Present

Cyberbullying Detection From Bangla Text on Social Media

Research Advances in Network Technologies (Volume 2), CRC Press

June 1, 2026 – Present

Machine Learning Engineer Certification

LinkedIn Learning

June 1, 2026 – Present

AFruitDB: A comprehensive dataset of six commonly used Asian fruits for advanced grading and biodiversity insights

ScienceDirect

June 1, 2026 – Present

Problem Solving (Basic) Certificate

HackerRank

June 1, 2026 – Present

Certificate of Participation (International Collegiate Programming Contest - ICPC)

Unknown

June 1, 2026 – Present

A Machine Learning-Based Approach to Predict the Effects of Video Games on Youth Behavior

19th INDIACom; 12th 2025 International Conference on Computing for Sustainable Global Development

January 1, 2025 – Present

Bangladeshi Local Fruits Detection and Calorie Calculator using CNN

18th INDIACom; 11th 2024 International Conference on Computing for Sustainable Global Development

January 1, 2024 – Present

Key Strengths

Strong academic background in Computer Science and Engineering with a focus on Data Science and Machine Learning.
Demonstrated experience in various academic projects related to deep learning, machine learning for prediction, and recommendation systems.
Multiple publications in relevant fields, indicating research capability and contribution to the domain.
Proficiency in Python, SQL, Git, and GitHub, essential tools for data science.
Experience with data processing techniques (handling missing values, encoding, normalization) and NLP techniques (tokenization, stopword removal).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's academic projects and publications demonstrate a strong interest and foundational knowledge in data science and machine learning, aligning well with a Data Science target role. The diversity of projects (image classification, medical prediction, recommendation systems, NLP for cyberbullying) indicates a broad interest within the field. Their involvement in research and participation in ICPC suggest a proactive and competitive spirit. However, the experience is primarily academic, and there is limited information on collaboration in a professional team environment.

Soft Skills & Operational Fit

The candidate's resume highlights problem-solving, critical thinking, and innovation, which are valuable soft skills for a Data Science role. Their academic background and research assistant experience suggest a structured approach to problem-solving and a commitment to data-driven solutions. However, without specific behavioral assessment data, it's difficult to fully assess operational fit regarding teamwork, stress handling, or adaptability in a professional setting.