Farhan Ali Awan

Academic

Career

Verbatim text

ABOUT ME 
I am a Data Science enthusiast with strong skills in Python, R, PostgreSQL, and Microsoft Excel. My expertise 
includes machine learning model development, data analysis, and visualization using tools such as Power BI, 
Matplotlib, and Seaborn, PySpark along with collaborative work in Google Colab. I am passionate about extracting 
actionable insights from data and building efficient, real-world solutions. With strong problem-solving abilities and a 
continuous learning mindset, I am committed to leveraging technology to make impactful contributions. 
 EDUCATION AND TRAINING 
07/02/2022 – CURRENT islamabad, Pakistan 
BACHELOR OF SCIENCE IN DATA SCIENCE Comsats University Islamabad 
Website https://www.comsats.edu.pk/  Level in EQF EQF level 6 
 
07/04/2019 – 06/06/2021 Islamabad, Pakistan 
FSC Scienta Vision College 
Website https://scientavision.edu.pk/  Level in EQF EQF level 4 
 WORK EXPERIENCE 
 BLUTECH CONSULTING BTC. – ISLAMABAD, PAKISTAN 
DATA ENGINEER INTERN – 13/07/2025 – 14/08/2025 
During my internship at BTC, I gained hands-on experience in data engineering by working with PostgreSQL, where I 
applied advanced SQL concepts such as window functions, indexing, and query optimization. I developed ETL 
pipelines using PySpark, incorporating techniques like Slowly Changing Dimensions (SCDs) and Change Data 
Capture (CDC) to manage historical and incremental data. This role strengthened my expertise in data warehousing, 
pipeline optimization, and big data processing, while improving my problem-solving and collaboration skills in a 
real-world environment. 
 SKILLS 
data extraction, transformation and loading tools 
ETL Pipelines 
machine learning 
Microsoft Word
 
Microsoft Excel Python (Pandas, Numpy, Matplotlib, Scipy, 
PySpark) 
 No SQL(Mongo DB) 
Languages 
PostgreSQL 
SQL 
R 
Python (computer programming) 
Data Visualization 
Power BI 
 PROJECTS 
20/03/2025 – 25/03/2025 
Twitter Sentiment Analysis Using CNN & Machine Learning Models 
Developed a sentiment analysis model to classify tweets as positive or negative using NLP techniques. The project 
involved data preprocessing, tokenization, stopword removal, lemmatization, and TF-IDF vectorization. Experimented with 
Bernoulli Naïve Bayes, SVM, and Logistic Regression, selecting the best-performing model. Additionally, implemented a 
CNN-based deep learning model to improve classification accuracy. The final system provides real-time insights into public 
sentiment on social media platforms. 
 
Farhan Ali Awan 
 
 Pakistani 
 Male 
 
 
 
 
 
Website:  https://pk.linkedin.com/in/farhan-ali-0b4282259 
Address: House No 39 St 93, 44220, Islamabad, Pakistan (Home) 
102

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