VAISHNAVI METKAR

Data Science

https://www.opentalent.in/vaishnavi-metkar

Data Science with less than a year in Python, SQL, and Power BI, eager to apply data-driven insights

Key Strengths

Strong academic background in Statistics (B.Sc. and M.Sc.) providing a solid theoretical foundation for Data Science.
Demonstrated practical application of machine learning models (Logistic Regression, Random Forest, XGBoost, ARIMA) in academic projects.
Proficiency in data manipulation and analysis using Python (Pandas, NumPy, Scikit-learn) and SQL.
Experience with data visualization and dashboard creation using Power BI, including DAX and Power Query.
Ability to perform exploratory data analysis (EDA), statistical analysis, and hypothesis testing.
Familiarity with model evaluation metrics (RMSE, MAE, R2, Accuracy, Precision, Recall, F1 Score, ROC-AUC) and interpretability techniques (SHAP).

Cultural & Operational Fit

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.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

About

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.

Top Skills

PythonDAXStar Schema

Projects

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.

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.

Key Strengths

Strong academic background in Statistics (B.Sc. and M.Sc.) providing a solid theoretical foundation for Data Science.
Demonstrated practical application of machine learning models (Logistic Regression, Random Forest, XGBoost, ARIMA) in academic projects.
Proficiency in data manipulation and analysis using Python (Pandas, NumPy, Scikit-learn) and SQL.
Experience with data visualization and dashboard creation using Power BI, including DAX and Power Query.
Ability to perform exploratory data analysis (EDA), statistical analysis, and hypothesis testing.
Familiarity with model evaluation metrics (RMSE, MAE, R2, Accuracy, Precision, Recall, F1 Score, ROC-AUC) and interpretability techniques (SHAP).

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

VAISHNAVI METKAR

Key Strengths

Cultural & Operational Fit

About

Top Skills

Skills

Education

Projects

Certifications

Key Strengths

Cultural & Operational Fit