About Me
Data Analyst with around 5 years of experience in transforming raw data into actionable insights to drive informed business decisions. Skilled in end-to-end data processes including data collection, cleansing, integration, and analysis using modern tools and programming techniques. Proficient in SQL, Python, and data visualization tools like Tableau and Power BI, with a strong ability to design interactive dashboards that clearly communicate KPIs and guide non-technical stakeholders.
Technical Skills
Language and Tools
Data Analysis & Modeling
Visualization Tools
Packages
Database Technologies
Data Platforms / Warehousing
Cloud Technologies
Professional Experience
- Automated end-to-end data pipelines using Python and Azure Data Factory, cutting manual data preparation time by 50%.
- Designed and implemented comprehensive Power BI dashboards that provided real-time, actionable financial and operational insights, improving visibility into key metrics by over 30%.
- Leveraged regression analysis and A/B testing to identify customer behavior trends, leading to a 25% increase in customer retention.
- Built and deployed advanced time-series forecasting models (ARIMA) to improve supply chain planning accuracy, reducing inventory holding costs by 20%.
- Created automated data validation frameworks using SQL and Python, which reduced reporting errors by 35%.
- Partnered with finance, operations, and marketing teams to translate complex datasets into actionable insights, resulting in a 12% revenue increase.
- Engineered scalable data pipelines with Apache Airflow and Python, speeding up data processing times by 45%.
- Developed customer segmentation models using Scikit-learn, increasing marketing campaign success rates by 25% and boosting customer retention by 15%.
- Delivered Power BI dashboards connected to Snowflake, improving team efficiency by over 30%.
- Applied time-series forecasting models (ARIMA) to enhance demand planning, resulting in an 18% reduction in inventory costs.
- Implemented anomaly detection algorithms (Isolation Forest) to identify fraudulent activities, cutting financial losses by 18%.
- Strengthened data governance by managing dbt transformations and automating quality checks, reducing data errors by 40%.
- Streamlined complex ETL workflows using Python and SQL, reducing manual data entry by 50%.
- Architected interactive Tableau dashboards to track key business performance metrics, cutting decision-making time by over 30%.
- Conducted regression and hypothesis testing on marketing datasets, leading to a 20% increase in campaign effectiveness.
- Cleaned and transformed large datasets with Pandas and NumPy, ensuring data integrity for in-depth analysis.
- Constructed automated data quality validation scripts using SQL, reducing data errors by 35%.
Projects
Here are a few examples of projects I've worked on. These can be replaced with your actual work.
Developed a predictive model using logistic regression and random forests to identify customers at high risk of churn. The model achieved 85% accuracy, enabling proactive retention campaigns.
Designed and built an interactive sales dashboard in Tableau to visualize key performance indicators (KPIs), sales trends, and regional performance. This provided leadership with actionable insights, leading to a 10% increase in quarterly sales.
Analyzed supply chain data to identify bottlenecks and inefficiencies. Implemented a time-series forecasting model to predict demand, reducing inventory costs by 15% and improving order fulfillment rates.