Mohd Shoeb Taj

MOHD SHOEB TAJ Hyderabad, Telangana, India. 500006 - | -| mohdshoebtaj | Shoebtaj22 Career Objective An aspiring Data Scientist with a strong foundation in Mathematics and Computer Science, equipped with a commitment to ongoing learning and growth. Proficient in Data Analysis, Machine Learning, and Data Visualization, with a skill set encompassing Python, R, and various Machine Learning Frameworks. Demonstrated success in translating raw data into actionable insights, creating predictive models, and effectively communicating findings. Eager to apply these skills to address real-world challenges and contribute to data-driven decisionmaking within an organization. Skills Summary Languages: C, Java, Python, R, SQL Frameworks & Libraries: Pandas, NumPy, Scikit-Learn, Matplotlib, TensorFlow, Keras Tools: Excel, PowerPoint, Tableau, MySQL, AWS(EC2,S3) Platforms: Jupyter Notebook, Visual Studio Code, PyCharm Soft Skills: Decision-making, Time Management, Attention to detail, Problem Solving. Education ● B.E in Computer Science Engineering (Data Science) December 2021 – August 2025 Lords Institute of Engineering and Technology Hyderabad, India ● Higher Secondary Certificate (Intermediate) June 2019 – March 2021 ● Narayana Junior College Secondary School Certificate (SSC) Hyderabad, India May 2018 – March 2019 Krishnaveni Talent School Hyderabad, India Work Experience Student Intern |IIUM (Malaysia) December 2024 (1 Week) • Explored in-depth concepts of Artificial Intelligence and machine learning, gained hands-on experience of IIUM Labs particularly in the department of Centre for Unmanned Technologies (CUTe) • Got an international exposure on AI & Robotics Industry, innovative technology driven solutions to real-life problems Swecha Summer Intern | Swecha May 2024 – June 2024 • Contributed to the "AI Creators Program" at Swecha, which resulted in developing an advanced Telugu Language Model (LLM) and a custom Text-to-Speech model. • Built and trained a Voice Avatar, which implemented AI-driven solutions for linguistic and speech applications. Business Analyst Intern | TouchPoint August 2023 – September 2023 Project Description: Analyzed a dataset consisting of car specifications, insurance risk ratings, and normalized loss data, which included a unique risk factor symbol assigned to each car that was adjusted based on its perceived risk level. • Conducted data cleaning, preprocessing, and Exploratory Data Analysis (EDA) on automobile datasets to extract actionable insights. • Developed and implemented analytical models in Python to optimize decision-making and improve operational efficiency. • Utilized statistical techniques and visualizations to identify patterns, inform business strategies, and enhance risk assessment. AWS Intern | Samfas Lab May 2023 – July 2023 • Applied the concepts of Cloud Computing, learned benefits and its implementation in modern enterprises. • Learned various cloud-based services mainly EC2, S3, IAM and VPC. • Developed Web Server using Django Framework integrated with cloud based EC2 machine. ·Used the equipment of the LAB available and completed the project with limited available resources. Projects 1. A Novel Hybrid Deep Learning Method for Early Detection of Lung Cancer using Neural Networks: • Currently working on a project which aims to detect Lung Tumors in their early stages with the help of advanced Deep Learning Techniques. • Initially, the UNET algorithm is utilized for accurate segmentation of cancer cells, enabling the identification of tumor boundaries. • Following this, the CCDC-HNN (Cancer Cell Detection using Hybrid Neural Network) algorithm classifies the segmented cells based on their features • Technologies: CNN, TensorFlow, Keras, Deep Learning, Amazon Web Services, Nvidia GPU Programming 2. Credit Card Fraud Detection: • Designed and optimized a logistic regression model to detect fraudulent credit card transactions, achieving an accuracy of 87%. • Addressed class imbalance using under-sampling and ensemble techniques, boosting model performance by 15%. • Conducted feature engineering and hyperparameter tuning, reducing false positives by 16% and enhancing model efficiency by 23%, resulting in a 6% improvement in overall accuracy. Technologies: Python, Scikit-learn, Pandas, NumPy, Matplotlib, Imbalanced-learn, Jupyter Notebook. Certifications NPTEL | Courses July 2023 – October 2024 • Secured consolidated score of 88% in Foundations of R Software. • Secured consolidated score of 72% in Data Science for Engineers. • Secured consolidated score of 64% in Advanced R Programming for Data Analytics in Business. IBM | IBM Data Science Professional Certificate July 2022 - December 2022 Extracurricular Activities ● Active Member and NSS Volunteer March 2023 - Present Contributed to community service projects, promoting social welfare and teamwork through various initiatives under the National Service Scheme (NSS). ● Merit Student of the Year July 2023