Data Analyst and Project Manager specializing in Python, SQL, machine learning, and statistical modeling to drive business decisions.
Highly analytical Data Analyst and Project Manager with expertise in Python, SQL, machine learning (Scikit-learn, TensorFlow), and statistical modeling. Adept at data visualization (Power BI, Tableau, Seaborn) and building predictive models for HR analytics, healthcare diagnostics, fraud detection, and NLP tasks.
Skilled in project planning, risk management, and stakeholder communication. Passionate about leveraging data science and project management to drive actionable business decisions.
Islamabad, Pakistan
fouziaashfaq0298@gmail.com
+92-3060651952
Developed a predictive analytics solution to forecast employee attrition and help HR teams retain talent effectively.
Built a high-accuracy churn model and provided actionable insights to improve retention strategies; results were visualized via interactive dashboards.
Built a text summarization system to extract key information from lengthy articles using NLP techniques and the TextRank algorithm.
Designed and implemented a working summarization tool capable of condensing long-form content while preserving core meaning; integrated into a web application for accessibility.
Created a sentiment analysis tool to classify movie reviews as positive or negative using NLP and logistic regression.
Trained a classifier with 88.87% accuracy; provided insights on improving model scalability and performance for future use.
Constructed a predictive model to assess the likelihood of diabetes onset in patients using clinical health indicators.
A medical prediction model with AUC-ROC: 0.89, providing actionable insights for early disease detection.
Performed exploratory data analysis on the Titanic dataset to understand survival patterns and relationships between passenger characteristics.
Discovered meaningful trends such as gender, class, and family size impacting survival rates; communicated findings visually and clearly.
Developed a time series forecasting model using ARIMA to predict website traffic trends over time, enabling better planning and resource allocation.
Successfully built and tuned an ARIMA model that provided accurate short-term traffic forecasts, visualized using Matplotlib for clear insights.
Analyzed the Boston housing dataset to uncover key factors affecting property prices and developed a regression model for price prediction.
Identified significant variables influencing house prices and created a predictive model to support real estate decision-making and investment strategies.
Created a machine learning system to predict loan defaults based on historical borrower data, helping financial institutions mitigate risk and reduce losses.
Trained and evaluated multiple models to identify high-risk borrowers; deployed a functional prototype with a user interface for real-time predictions.
Developed a fraud detection pipeline for credit card transactions using the Credit Card Fraud dataset, handling imbalanced data with SMOTE and training a Random Forest model.
A fraud detection pipeline with 90% recall, ensuring accurate identification of fraudulent transactions.
Excelerate
May 2025 - Present
Skills: Python (Pandas, Scikit-learn), NLP (spaCy, BERT), SQL, GitHub, Matplotlib, Data Visualization
Excelerate
May 2025 - Present
Forage
May 2025
Forage
Apr 2025
Forage
Apr 2025
DevelopersHub Corporation
Mar 2025 – Apr 2025
Comsats Islamabad
Jan 2022 - May 2025
Advanced studies in applied mathematics with focus on statistical modeling and data analysis techniques.
University of Sargodha
Sept 2016 - Sept 2020
Bachelor's degree in Mathematics with GPA: 3.25. Coursework included statistical analysis, calculus, and mathematical modeling.
WsCube Tech
May 2025
Kaggle
May 2025
April 2025
WsCube Tech
April 2025
WsCube Tech
April 2025
April 2025
Google Digital Academy (Skillshop)
March 2025
British Council
January 2021