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Data Science with less than a year in NLP & Data Engineering
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Motivated and detail-oriented Data Science graduate student in the final semester of an MS in Data Science at SZABIST Islamabad, with a BSCS foundation from COMSATS University. Passionate about NLP, machine learning, and data engineering pipelines. Seeking an internship at FAST-NUCES Islamabad to apply hands-on skills in Python, SQL, Spark, and deep learning to real-world data challenges.
SZABIST Islamabad
MS · Data Science
August 1, 2025 – June 30, 2026
COMSATS University Islamabad
BS · Computer Science
August 1, 2011 – June 30, 2015
Facial Emotion Recognition (MS Thesis)
January 1, 2025 – January 1, 2026
Designed a hybrid deep learning model combining CNN-based spatial feature extraction with LSTM temporal modeling. Trained and evaluated on benchmark datasets (FER2013, CK+); achieved competitive accuracy improvements.
Exercise Monitoring System (BSCS FYP)
January 1, 2014 – January 1, 2015
Developed an Android app + web dashboard for tracking physical exercise metrics using mobile sensors. Backend built with Java; data stored and queried via SQL database.
Python for Data Science & AI
Coursera / edX
January 1, 2026 – Present
Machine Learning specialization coursework
SZABIST
January 1, 2026 – Present
Big Data & Spark training
SZABIST
January 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a blend of traditional software development (Android app with Java/SQL) and advanced data science (Deep Learning for emotion recognition). This diversity, coupled with a clear focus on Data Science and ML, aligns well with roles requiring both foundational engineering skills and specialized ML expertise. The pursuit of an MS in Data Science after a career break shows strong commitment and adaptability. However, the lack of professional experience outside of academia might require additional mentorship for integration into a corporate environment.
Soft Skills & Operational Fit
The candidate's resume indicates a motivated and detail-oriented individual with a strong passion for NLP, machine learning, and data engineering. The career break and subsequent return to academia with a strong focus on data science suggest resilience and a clear career direction. However, without specific psychometric or English test scores, it's difficult to assess logical reasoning, work attitude, stress handling, or team collaboration skills. The professional summary is clear and concise, indicating good written communication.