Data Analyst Power Bi

Swaroop Reddy Data Analyst

*******@***********.*** 979-***-**** Austin, TX LinkedIn

Summary

Strategic and detail-focused Data Analyst with 3+ years of expertise in transforming complex data into actionable insights in finance, supply chain, and healthcare. Skilled in SQL, Python, and Power BI to streamline processes, reduce inefficiencies, and enhance decision-making accuracy. Adept at building scalable data pipelines, automating ETL workflows, and crafting data- driven strategies that optimize risk and resource management. Experienced in collaborating with cross-functional teams to solve complex problems, drive measurable results, and support strategic business goals. Education

Master of Science in Data Analytics Texas, USA

The University of Texas at Arlington

Bachelor of Technology in Information Technology Vellore, India Vellore Institute of Technology

Technical Skills

• Programming Languages: Python (NumPy, Pandas, SciPy, Statsmodels), SQL, R

• Data Visualization: Power BI, Tableau, Looker Studio, Plotly, Seaborn

• Database Management: MySQL, PostgreSQL, AWS Redshift, Google BigQuery, Snowflake

• Cloud Platforms: AWS (S3, Glue, Redshift), GCP (BigQuery, Looker Studio), Azure (Data Lake, HDInsight)

• Advanced Analytics: Predictive Modeling, Statistical Analysis, Regression Testing, Risk Assessment, ETL

• Tools: Google Analytics (GA4), Jupyter Notebooks, Excel (Advanced Functions, Power Query, VBA), SAS Professional Experience

Data Analyst, BNY Mellon 05/2023 – Present Remote, USA

• Aggregated and prepared large-scale transactional data using SQL, streamlining datasets for advanced risk analysis.

• Performed EDA and applied regression and hypothesis testing, uncovering trends and reducing errors by 15%.

• Built predictive models with Monte Carlo simulations, optimizing performance and reducing portfolio volatility by 15%.

• Designed interactive dashboards in Power BI, improving stakeholder decision-making efficiency by 20%.

• Developed scalable data pipelines using AWS Glue and Redshift, improving data processing times by 25% and Performed stress testing and scenario analysis to optimize portfolio resilience.

• Conducted scenario analysis to evaluate portfolio resilience, leading to recommendations that improved risk mitigation strategies by 20%.

Data Analyst, FedEx Supply Chain Services 05/2020 – 12/2021 India

• Led over 10 marketing campaigns, analyzing performance and optimizing strategies using Google Analytics, resulting in a 30% increase in campaign effectiveness.

• Developed segmentation strategies with SQL, increasing customer engagement by 25% and conversion rates by 20%.

• Performed competitor analysis and market research, driving a 10% increase in market share.

• Developed 70+ dashboards in Tableau and Power BI, delivering actionable insights and improving decision-making by 25%.

• Partnered with sales and product teams to drive a 15% boost in sales performance.

• Utilized predictive analytics to optimize resource allocation, reducing marketing waste by 20%. Projects

Integrated Healthcare Data Analytics Platform

• Designed and implemented a data warehouse to consolidate patient records from multiple sources, leveraging SQL and Python for seamless data integration.

• Automated ETL processes using AWS Glue and Redshift, reducing data preparation time by 40% and ensuring real-time analytics capability.

• Built Power BI dashboards to visualize critical healthcare metrics, leading to a 20% reduction in patient wait times and improved resource allocation.

Predictive Energy Modeling for Operational Efficiency

• Developed linear regression models in Python to predict net hourly electrical output based on environmental variables, improving forecasting accuracy.

• Conducted p-value analysis and ANOVA to address multicollinearity and ensure model reliability. Streamlined Retail Database Management System

• Designed a MySQL database for Arlington Sprouts Store, reducing data retrieval times by 20%.

• Built a Python-based web interface with enhanced security, increasing customer satisfaction by 30%.

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