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Data Science with less than a year in Data Analysis & Machine Learning
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Assessing your cultural and operational fit
Economics graduate and MS Business Analytics student with a strong interest in data analysis, business strategy, and financial decision-making. Skilled in Python, SQL, statistical analysis, and machine learning, with experience working on projects related to finance, ESG, e-commerce, and supply chain analytics. I enjoy working with data to find patterns, solve problems, and support better business decisions. My background in banking has also helped me develop a practical understanding of financial operations and customer needs. I am looking to build my career in data analytics, business intelligence, or financial analytics, where I can combine technical skills with business knowledge to create value.
FAST University (FAST-NUCES)
Master of Science · Business Analytics (MSBA)
August 1, 2025 – June 30, 2027
Bahria University
Bachelor of Science · Economics
August 1, 2018 – June 30, 2022
Bank Makrammah Limited
Banking Intern
June 1, 2021 – August 1, 2021
Islamabad, Islamabad Capital Territory, Pakistan
E-Commerce Ecosystem Analytics
June 1, 2026 – Present
Built a Python-based framework to detect revenue leakage and predict delivery lead times using feature engineering and Scikit-Learn predictive models. Delivered actionable insights on logistics bottlenecks and supplier performance for an international e-commerce platform.
Financial Database System - Pakistan Textile Sector
June 1, 2026 – Present
Designed and implemented a normalized relational database (3NF) to analyze quarterly financial ratios of Sapphire, Nishat, and Kohinoor Textile Mills. Wrote advanced SQL queries for profitability ranking, liquidity comparison, and trend analysis; built ERD in MySQL Workbench with BI dashboard visualizations.
Impact of COVID-19 on Pakistan's Economy
June 1, 2026 – Present
Analyzed macroeconomic impacts of COVID-19 on Pakistan's GDP, trade, employment, and key sectors using econometric models and secondary data sources.
Supplier Delivery Performance Monitor
June 1, 2026 – Present
Built a Python monitoring system to evaluate supplier on-time delivery rates, flag underperforming vendors, and surface trend insights for supply chain optimization.
The ESG-Financial Performance Nexus
June 1, 2026 – Present
Investigated causal relationships between ESG performance and corporate financial outcomes across Asia, US, and EU markets using panel econometrics and ML. Applied XGBoost and SHAP-based Explainable AI to identify key ESG drivers of financial performance with interpretable model outputs.
Comprehensive Statistical Analysis of Adidas Sales
June 1, 2026 – Present
Performed descriptive statistics, hypothesis testing, correlation analysis, and regression modeling on Adidas global sales data. Identified key performance drivers across regions, product categories, and sales channels to support strategic recommendations.
Self-study: Python for Data Analysis, Machine Learning and SQL querying for business use cases.
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a broad interest in various analytical applications, from financial analysis to supply chain optimization and ESG. This diversity suggests adaptability and a willingness to tackle different types of business problems. The target role of Data Science aligns well with the candidate's MSBA coursework and project experience. The self-study initiative also shows proactivity and a commitment to continuous learning, which are positive indicators for cultural fit in a dynamic technical environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work with data to solve problems and support business decisions, suggesting a problem-solving mindset. The mention of 'active participant in community development and social impact initiatives' hints at teamwork and social responsibility, which are positive soft skills. However, the internship was administrative and customer-service focused, providing limited insight into operational fit for a senior data science role.