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Data Science with less than a year in financial modeling and data analysis.
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Assessing your cultural and operational fit
Finance analyst with internship experience at the Ministry of Finance and Agritech, skilled in financial modeling, data analysis and visualization using Excel, Power BI and SQL. Proven ability to streamline reporting processes and develop dashboards that deliver actionable insights. Adept at interpreting complex financial data, collaborating across teams, and driving process efficiencies through automation.
Namal University
Bachelor of Business Administration · Business Administration
September 1, 2022 – Present
Ministry of Finance, Finance Division
Internship
July 1, 2025 – August 31, 2025
Islamabad, Islamabad Capital Territory, Pakistan
Lahore University of Management Sciences (LUMS)
Remote Internship
March 1, 2025 – April 30, 2025
India
Agritech (Pak-American Fertilizer Limited)
Internship
August 1, 2024 – September 30, 2024
Pakistan
Sugarcane Varieties identification Project
June 19, 2026 – Present
Utilized R and Excel to collect and analyze sugarcane variety data, collaborating with industry experts to deliver actionable insights on sustainable crop practices
Coffee Shop Sales Dashboard (Excel)
June 19, 2026 – Present
Developed an interactive Excel dashboard using pivot tables and VBA to visualize sales trends, peak hours, and top-selling products, enhancing strategic decision-making
Extrovert vs. Introvert Personality Traits (R-Studio)
June 19, 2026 – Present
Analyzed behavioral data using logistic regression in R topredict personality types and identify key patterns
Breast Cancer Detection using Machine Learning
June 19, 2026 – Present
Developed and compared ML models (Logistic Regression,KNN, SVM) for breast cancer detection to identify the bestperforming classifier
Machine Learning Scientist Track (Python)
Unknown
June 1, 2026 – Present
Introduction to PowerBI
Unknown
June 1, 2026 – Present
SQL for business analytics: DataCamp
DataCamp
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate an interest in diverse applications of data science, from agricultural insights to healthcare and behavioral analysis. The internships, though not directly in data science, show exposure to different organizational cultures (government, research, corporate). This breadth suggests adaptability. However, the experience level is very junior, and the projects are primarily academic, which might require significant mentorship to align with a senior-level industry role. The target role of 'Data Science' is broad, and the candidate's current profile aligns more with an entry-level data analyst or junior data scientist.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to collaborate with industry experts and engage with communities, suggesting potential for teamwork and communication. The internship experiences, while not directly technical, show exposure to structured work environments and an ability to support operational tasks. However, the descriptions lack specific details on problem-solving approaches or contributions to complex operational challenges, making it difficult to fully assess advanced soft skills and operational fit.