mahiya afreen

Entry-level Data Analyst

Hyderabad, India 80 · Excellent

About

Computer Engineering graduate with hands-on experience in data analysis, Python-based data pipelines, and dashboard development. Passionate about translating campaign and business data into actionable insights. Seeking an entry-level Data Analyst role to apply analytical skills, data visualization expertise, and a growth mindset to support campaign performance and business outcomes.

Skills & Expertise (21)

Python Intermediate

6.5/10

Years Exp

NumPy Intermediate

6.0/10

Years Exp

Pandas Intermediate

6.0/10

Years Exp

scikit-learn Intermediate

6.0/10

Years Exp

Data Preprocessing Intermediate

6.0/10

Years Exp

Exploratory data analysis Intermediate

6.0/10

Years Exp

Tableau Intermediate

6.0/10

Years Exp

Excel Intermediate

6.0/10

Years Exp

SQL Intermediate

5.5/10

Years Exp

Matplotlib Intermediate

5.0/10

Years Exp

Seaborn Intermediate

5.0/10

Years Exp

BigQuery Beginner

4.0/10

Google Cloud Platform Beginner

4.0/10

Java Beginner

3.0/10

CSS Beginner

3.0/10

HTML Beginner

3.0/10

JavaScript Beginner

3.0/10

Flask Beginner

2.5/10

AES Beginner

2.0/10

SQLite Power BI

Work Experience

Data Analytics Simulation

Deloitte Australia (via Forage)

Jan 2026 - Jan 2026

Completed a forensic technology and data analytics simulation replicating industry-level campaign analysis tasks. Designed and built an interactive Tableau dashboard to track and visualize key business performance metrics. Used Excel for data classification, pattern identification, and drawing business conclusions from raw datasets. Strengthened understanding of campaign analytics processes, stakeholder reporting, and analytics documentation practices.

Data Science Intern

EISystems Services

May 2025 - May 2025

Performed end-to-end data analysis including data cleaning, preprocessing, and exploratory data analysis (EDA) using Python (NumPy, Pandas). Extracted actionable insights from structured datasets; communicated findings to support business decision-making. Built and evaluated machine learning models using Scikit-learn and interpreted results for non-technical stakeholders. Gained hands-on exposure to the full data science lifecycle, including documentation and reporting of methodologies.