Data Analyst with less than a year in data visualization, ETL, and machine learning
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
I'm a passionate and detail-oriented Data Analyst, Data Engineer, and Data Scientist with hands-on experience in building interactive dashboards and data-driven projects using Power BI, Excel, Python, SQL, MySQL, and R. Skilled in data visualization, ETL processes, machine learning, NLP, and time series forecasting, I focus on turning raw data into clear, meaningful insights and business solutions.
COMSATS University Islamabad, Lahore Campus
BS Statistics · Data Sciences
September 1, 2023 – July 1, 2027
Global Amazon Dashboard
December 1, 2025 – June 1, 2026
Created a Power BI dashboard using Excel data to analyze sales, profit, customer trends, and product returns (2012-2015). Identified key insights such as total sales of $12.64M, highest contribution from the Consumer segment (51%), and Asia Pacific as the top market (32%). Built interactive visuals using charts, KPIs, and filters for easy data exploration. Designed the dashboard to support clear and effective business decision-making. Applied data transformation and modeling for structured and accurate reporting.
Employee Performance Analysis
December 1, 2025 – June 1, 2026
Cleaned and transformed employee data using Pandas. Analyzed salary trends by department and gender. Created visualizations using Seaborn, Matplotlib, and Plotly. Performed Exploratory Data Analysis (EDA) on key variables.
Freelancer Earnings Analysis
December 1, 2025 – June 1, 2026
Built an interactive, Power BI-style dashboard in R Shiny using data from a MySQL database. Designed and developed visual analytics for freelancer earnings to understand trends and patterns. Created interactive charts such as heatmaps, maps, funnels, and boxplots using Plotly and ggplot2. Added dynamic filters and region-based insights for better exploration of data. Focused on making data easy to understand for better decision-making.
PM2.5 Air Quality Forecasting Model
December 1, 2025 – June 1, 2026
Built a time series forecasting model using ARIMA to predict PM2.5 air pollution levels in Islamabad, Pakistan. Achieved around 89% accuracy in forecasting air quality for the next 30 days through model tuning and statistical analysis. Improved Model Performance through validation and optimization. Presented this research at Islamabad Datafest 2025 in a poster competition.
Sales & Profit Analysis
December 1, 2025 – June 1, 2026
Built an interactive sales and profit dashboard using Microsoft Excel. Used pivot tables to analyze top products, customers, and yearly trends. Created charts to clearly visualize sales, profit, and quantity performance. Added slicers for easy and interactive data filtering. Used Excel formulas and GETPIVOTDATA for dynamic reporting. Focused on making data simple and easy to understand for decision-making.
Amazon Fine Food Reviews Sentiment Analysis
December 1, 2025 – June 1, 2026
Developed an NLP-based sentiment analysis project using VADER and RoBERTa models. Cleaned and processed large-scale customer review data with preprocessing and EDA. Compared lexicon-based and transformer-based models using statistical evaluation metrics. Visualized sentiment trends, word clouds, and customer feedback insights. Applied Hugging Face RoBERTa model for context-aware sentiment prediction.
Data Warehousing
DataCamp
December 1, 2025 – Present
Introduction to Snowflake
DataCamp
December 1, 2025 – Present
Associate Data Engineer in SQL
DataCamp
December 1, 2025 – Present
Understanding Data Visualization
DataCamp
December 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a broad interest in various data analysis domains, including sales, environmental forecasting, and sentiment analysis. The involvement in a university statistical society and participation in a datafest suggest a proactive and engaged approach to learning and community involvement, which aligns with a collaborative and growth-oriented culture. The diverse toolset (Python, R, SQL, Power BI, Excel) indicates adaptability. However, all projects are academic, and there is no professional experience, which limits the assessment of cultural fit in a corporate environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a focus on making data 'easy to understand for better decision-making,' suggesting an inclination towards clear communication of insights. Participation in Datafest and a role as 'Director of Learning' hint at collaboration and a proactive learning attitude. However, without direct behavioral assessment, specific soft skills and operational fit cannot be fully determined.