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Data Science with less than a year in Python, SQL, and Power BI, eager to apply data-driven insights
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
M.Sc. Statistics graduate with a strong foundation in statistical analysis, data interpretation, and exploratory data analysis. Skilled in Python, SQL, Excel, and Power BI for analyzing datasets, building dashboards, and generating actionable business insights. Experienced in data cleaning, hypothesis testing, and visualization through academic projects. Passionate about applying statistical and analytical skills to solve real-world business problems and contribute to data-driven decision-making.
Unknown
Master of Science (M.Sc.) · Statistics
January 1, 2023 – January 1, 2025
Unknown
Bachelor of Science (B.Sc.) · Statistics
January 1, 2020 – January 1, 2023
Global Superstore Sales Forecasting & Customer Segmentation
June 24, 2026 – Present
Analyzed 50,000+ retail transactions using Python, SQL, and Power BI for data cleaning, EDA, and feature engineering. Built ARIMA, Random Forest, and XGBoost models for sales forecasting and profit prediction. Evaluated model performance using RMSE, MAE, and R2. Performed RFM analysis and K-Means clustering for customer segmentation. Developed Power BI dashboards to provide insights for pricing, inventory, and marketing decisions.
Customer Churn & Retention Analysis using Machine Learning
June 24, 2026 – Present
Processed telecom customer data using Python, SQL, and Power BI for preprocessing, EDA, and statistical analysis. Built Logistic Regression, Random Forest, and XGBoost models with SMOTE to predict churn. Evaluated performance using Accuracy, Precision, Recall, F1 Score, and ROC-AUC. Applied SHAP to identify key churn drivers and explain model predictions. Created dashboards to identify high-risk customers and recommend retention strategies.
Power BI Micro Course
Online Learning Program
January 1, 2025 – Present
Introduction to SQL
IBM
January 1, 2023 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a focus on practical applications of data science, which aligns with a results-oriented culture. The diversity of projects (churn analysis, sales forecasting, customer segmentation) shows a breadth of interest within the data science domain. However, the lack of professional experience or team-based project descriptions makes it challenging to assess collaboration style or fit within a fast-paced, agile environment. The candidate is currently pursuing a Master's degree, indicating a commitment to continuous learning.
Soft Skills & Operational Fit
The candidate's resume indicates a passion for applying statistical and analytical skills to solve real-world business problems, suggesting a problem-solving mindset. The academic project descriptions are clear and structured, implying good organizational skills. However, without specific work experience or behavioral assessment data, it is difficult to fully assess soft skills like teamwork, communication in a professional setting, or adaptability under pressure.