Looking for a job

Akansha singh

@akanshasingh3

Message

Aspiring data analyst specializing in SQL, Power BI, and Python-driven insights.

India

Message

What I'm looking for

I’m looking for an entry-level data analyst role where I can use SQL, Python (Pandas), and Power BI to clean data, build dashboards, and deliver KPI-driven insights—collaborating with cross-functional teams to support data-driven business decisions.

I’m an aspiring data analyst with hands-on experience in the end-to-end data lifecycle. I specialize in SQL database querying, Power BI data modeling, Advanced Excel, and Python (Pandas), focusing on transforming raw data into actionable business insights. I’m highly disciplined, with strong analytical thinking, attention to detail, and effective communication skills.

Through my projects, I’ve streamlined data extraction and structural data manipulation using SQL, and I’ve handled data cleaning and preprocessing with Python (Pandas) for unstructured logs and missing values. I built interactive Power BI dashboards with DAX basics, KPI reporting, and data visualization to track revenue and churn risk, while using Excel (Pivot Tables, XLOOKUP, VLOOKUP, and conditional formatting) to reduce preprocessing latency. I’m eager to collaborate with cross-functional teams and contribute to data-driven business solutions.

Experience

Work history, roles, and key accomplishments

Customer Churn Analysis

Bank

Used SQL and Python (Pandas) to extract and manage an international banking dataset of 4,000+ customers, building data cleaning models to handle missing values and demographics. Created an interactive Power BI dashboard with DAX and dynamic slicers to analyze risk metrics and identify 1,538 churned customers (38.45% churn rate), improving pipeline reliability by 45% and reducing preprocessing late

SQL Python Power BI DAX Data Cleaning Data Validation Data Modeling Dashboard Development Pivot Tables Conditional Formatting Slicer

Netflix User Data Analytics

Netflix

Streamlined the end-to-end data lifecycle for a Netflix streaming dataset of 3,000+ active users using SQL, Python (Pandas), and advanced Excel. Improved data quality by 45%, reduced data preparation latency by 30%, and built an interactive Power BI dashboard tracking $39,000 global revenue using DAX.