Help & Supportcareers@gravityer.com
Data Science with less than a year in Data Analysis & Machine Learning.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Science student with a strong foundation in machine learning and data analysis, actively building expertise through diverse personal projects. Proven ability to analyze complex datasets, develop recommendation systems, and create interactive data visualizations. Recognized for academic performance and contributions to data analysis workflows during an internship.
National University of Computer and Emerging Sciences (FAST-NUCES)
BS Data Science · Data Science
August 1, 2022 – June 30, 2026
Tapit Card
Business Analyst
June 1, 2025 – August 1, 2025
Islamabad, Islamabad Capital Territory, Pakistan
MedVisionAI
January 1, 2025 – June 1, 2025
Built a lightweight AI-powered chest X-ray learning platform using multimodal RAG (FAISS + LORA) for efficient knowledge retrieval on low-resource systems, reducing average query latency by 30% compared to a baseline retrieval approach. Implemented ethical AI principles, including explainability overlays and bias checks, to improve model interpretability; paired with adaptive flashcards that increased simulated user retention by 25% in pilot testing.
Tuberculosis Data Dashboard
January 1, 2024 – December 1, 2024
Engineered an interactive D3.js dashboard to visualize TB datasets across 50+ countries, uncovering regional trends that informed a 3-page analytical report. Designed drill-down visualizations that reduced data interpretation time for stakeholders by an estimated 35%.
Spotify Recommendation System
January 1, 2024 – December 1, 2024
Developed a real-time music recommendation system using Python, Kafka, and Spark, achieving sub-second recommendation latency for a dataset of 10,000+ tracks. Designed scalable data pipelines handling ingestion, transformation, and recommendation delivery, reducing pipeline processing time by 40%.
Near Real-Time Data Warehouse
January 1, 2024 – December 1, 2024
Architected a near real-time data warehouse in Python and MySQL using a hybrid join approach, processing streaming and batch data with 25% faster average query response time compared to the prior architecture. Optimized data pipelines for faster query performance and continuous data integration, supporting a team of 3 in maintaining data consistency across sources.
Cultural Fit Analysis
The candidate's project diversity, ranging from AI-powered medical platforms to music recommendation systems and data dashboards, indicates a broad interest and adaptability, which aligns well with dynamic team environments. Their academic background and awards suggest a drive for excellence. The internship experience, though brief, shows an ability to contribute to business objectives. The candidate's focus on practical applications and measurable outcomes in projects suggests a results-oriented mindset. However, with only one internship, the breadth of professional experience is limited.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical and problem-solving skills through their project work, particularly in optimizing data pipelines and reducing latency. Their internship as a Business Analyst shows collaboration with cross-functional teams and a focus on data-driven decision-making. The project descriptions indicate an ability to work independently and deliver measurable results. However, without specific psychometric test results, a deeper assessment of work attitude, stress handling, and team collaboration is limited.