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My name is Sana S. and I have over 5 years of experience in the tech industry. I specialize in the following technologies: Data Science, Algorithm Development, Machine Learning, Python, Neural Network, etc.. I hold a degree in Master of Computer Science (MSCS), Bachelor of Computer Science (BCompSc). Some of the notable projects I’ve worked on include: Sentiment Analysis of Movie Reviews, Optimized Scheduling Algorithm for Film Festival Web App, Python Modelling Expert. I am based in Shikarpur, Pakistan. I've successfully completed 3 projects while developing at Softaims.
I approach every technical challenge with a mindset geared toward engineering excellence and robust solution architecture. I thrive on translating complex business requirements into elegant, efficient, and maintainable outputs. My expertise lies in diagnosing and optimizing system performance, ensuring that the deliverables are fast, reliable, and future-proof.
The core of my work involves adopting best practices and a disciplined methodology, focusing on meticulous planning and thorough verification. I believe that sustainable solution development requires discipline and a deep commitment to quality from inception to deployment. At Softaims, I leverage these skills daily to build resilient systems that stand the test of time.
I am dedicated to making a tangible difference in client success. I prioritize clear communication and transparency throughout the development lifecycle to ensure every deliverable exceeds expectations.
Main technologies
AI, Machine Learning and Data Science Platforms
5 years
Data Science
4 Years
Algorithm Development
1 Year
Machine Learning
1 Year
Additional skills
- Data Science
- Algorithm Development
- Machine Learning
- Python
- Neural Network
- Tutoring
- Artificial Intelligence
- Machine Design
- Algorithms
- Computer Science
- Data Structures
- Deep Learning
- TensorFlow
- PyTorch
- Python Scikit-Learn
Direct hire
Potentially possible
Previous Company
Techlogix
Experience Highlights
Sentiment Analysis of Movie Reviews
Developed a machine learning model to classify movie reviews as positive, negative, or neutral. Utilized the IMDB movie review dataset and implemented a Random Forest classifier. The model achieved an accuracy of 82% in predicting sentiment, demonstrating its effectiveness in understanding and analyzing text-based data.
Optimized Scheduling Algorithm for Film Festival Web App
Optimized a Node.js scheduling algorithm for a film festival app, enhancing efficiency and accuracy. Improved the existing script by addressing constraints such as unique screenings, user-defined "Busy Times," and travel time management. Incorporated customizable buffer times and optional inclusion of lower-priority films. Achieved a more effective scheduling system that prioritized high-value screenings and minimized travel, significantly improving user satisfaction and overall scheduling performance.
Python Modelling Expert
a Python Modelling Expert to help us with logistic regression, knn and naive bayes estimation. The ideal candidate will have a strong background in Python and experience in statistical modelling techniques. This project involves building and evaluating predictive models using logistic regression and naive bayes algorithms. You will be responsible for data preprocessing, feature engineering, model training and evaluation. The successful candidate should be able to interpret the results and provide actionable insights based on the models. kidney disease modeling.
Education
NED University of Engineering and Technology
Master of Computer Science (MSCS) in Computer science
2020-01-01-2022-01-01
Institute of Business Administration
Bachelor of Computer Science (BCompSc) in Computer science
2016-01-01-2020-01-01
Languages
- English
- Panjabi, Punjabi
- Urdu
Github