Open to opportunities

Ashlesha User

@ashleshauser

Message

Data Analyst transforming data into actionable business insights with Python and BI.

India

Message

What I'm looking for

I’m looking for a role where I can build Python/SQL-based analytics and Power BI/Tableau dashboards that drive decisions—plus collaborate with teams that value continuous learning, clear KPI reporting, and turning complex data into business-ready insights.

I’m a Data Analyst with hands-on experience turning raw data into actionable business insights through data cleaning, exploratory analysis, statistical analysis, dashboard development, and KPI reporting. I’ve worked with large transactional and multi-source datasets—building end-to-end analytics solutions that support data-driven decisions.

Across my projects and virtual internships, I’ve analyzed customer retention and revenue concentration across quick-commerce order data, delivered interactive Power BI dashboards with DAX measures, and designed portfolio analytics pipelines using Python and the Yahoo Finance API. I also build machine-learning-driven models (e.g., logistic regression, fraud detection, and predictive analytics) when the problem calls for it, and I’m motivated by continuous learning, analytical thinking, and clear communication of insights.

Experience

Work history, roles, and key accomplishments

Data Analytics Virtual Internship

InLighnX Global Pvt. Ltd.

May 2025 - Aug 2025 (3 months)

Designed a dynamic Excel sales dashboard using Power Query, Power Pivot (DAX), and PivotTables to automate KPIs and provide time-based and product performance insights for management reporting. Built an HR attrition prediction model in Python using Scikit-Learn with Logistic Regression to identify high-risk employees for proactive retention planning.

Excel Power Query Power Pivot DAX Data Cleaning Feature Engineering Python scikit learn Logistic Regression KPI Reporting Dashboard Development

Data Science Virtual Internship

CodSoft

Oct 2024 - Nov 2024 (1 month)

Developed a Logistic Regression classification workflow on the Titanic dataset using feature engineering and model tuning, and implemented a credit card fraud detection pipeline addressing imbalanced data. Built a movie rating prediction model using regression techniques and evaluated models using metrics such as accuracy, ROC-AUC, PR-AUC, R², and RMSE.

Python Logistic Regression Feature Engineering VIF Analysis GridSearchCV Pandas NumPy scikit learn SMOTE Random Forest Decision Trees Target Encoding ROC AUC F1 Score PR AUC Accuracy

Education

Degrees, certifications, and relevant coursework

IIIT Bangalore

Executive Post Graduate Programme in Data Science & Artificial Intelligence, Data Science & Artificial Intelligence

2024 - 2025

Grade: GPA: 3.91

Completed an Executive Post Graduate Programme in Data Science & Artificial Intelligence with specialization in Data Analytics and Business Intelligence.