Data Analyst Power Bi

Sai Sravya Pallothu United States

Data Analyst 682-***-****

************@*****.***

https://www.linkedin.com/in/sai-sravya-pallothu/

Professional Summary

Data Analyst with 3 years of experience in SQL, Python, R, and advanced analytics, delivering data-driven solutions across financial services and banking.

I am skilled in designing ETL pipelines, data warehouses, and automated reporting using Azure Data Factory, SSIS, and AWS.

Proficient in Tableau, Power BI, and Excel for building interactive dashboards that improve executive decision- making and regulatory compliance.

Experienced in predictive modeling, statistical analysis, and machine learning techniques to optimize risk management, fraud detection, and customer retention.

Adept at leveraging Snowflake and collaborating with stakeholders to translate business needs into scalable analytics solutions that drive measurable impact.

Hands-on experience working with cross-functional teams to deliver end-to-end analytics solutions, from data extraction to executive-level reporting.

Skills

Core Analytics & Programming: SQL, Python, R, Excel (Advanced Functions, VBA, Power Query, DAX), PySpark, MATLAB, SAS, Hadoop, Scala, Pandas, NumPy

Visualization & BI Tools: Power BI, Tableau, Looker, QlikView, Google Data Studio, RStudio

Databases & Cloud Platforms: SQL Server, PostgreSQL, Oracle, Snowflake, Databricks, AWS (Redshift, S3), Azure (Data Factory, Data Lake), GCP (BigQuery, DataFlow)

Statistical & Analytical Techniques: Regression Analysis, Forecasting, Time Series Analysis, A/B Testing, Hypothesis Testing, Variance Analysis, Chi-Square Test, T-Test, ANOVA, Multivariate Testing,

Data Management & ETL: Data Warehousing, ETL Pipelines (SSIS, ADF), Data Modeling, Data Governance, Data Quality, AWS Glue

Business & Reporting Tools: KPI Development, Financial Analysis, Risk Analysis, SSRS, Advanced Excel Reporting

Data Visualization Libraries: Matplotlib, Seaborn, Plotly, ggplot2, Power Query, DAX

Reporting & Documentation: SSRS, Crystal Reports, Advanced Excel Reporting, Technical Documentation, Process Workflow Documentation, Executive Reporting (Dashboards, Presentations, Storytelling)

Collaboration & Project Tools: JIRA, Confluence, Trello, MS Project, Agile, Scrum Experience

Data Analyst BNY Mellon, TX, USA Sep 2024 – Present Description: BNY Mellon is a global investment management and investment services company. Responsible for advanced data analysis, statistical modeling, business intelligence, financial analysis, and providing actionable insights to support strategic decision-making and business growth.

Designed and delivered Power BI dashboards that consolidated portfolio performance and risk metrics, enabling executives to access real-time insights and accelerating decision-making by 20%.

Streamlined regulatory compliance reporting (CCAR, Basel III, DFAST) by automating SQL workflows, which reduced repetitive manual work by 35% and minimized errors in submission.

Conducted in-depth trading data analysis using Python, R, and SQL to detect anomalies and market trends, providing actionable insights that improved trading strategy efficiency by 15%.

Built credit scoring reports leveraging statistical and ML techniques, which improved the accuracy of loan approval decisions by 12% and reduced approval turnaround times.

Leveraged PySpark with AWS to process and analyze millions of trading records, reducing data processing time and enabling faster anomaly detection while improving the accuracy of risk and performance analytics.

Automated ETL pipelines with SQL and Power Query to standardize data preparation across teams, cutting processing time by 25% and ensuring consistency in reporting datasets.

Created KPI scorecards for senior leadership to track progress against strategic objectives, improving visibility into performance metrics across multiple business units.

Implemented data validation and quality checks in SQL and Python, which enhanced compliance data accuracy by 25% and ensured reliability for regulatory submissions.

Partnered closely with risk and finance teams to translate reporting requirements into scalable BI solutions, aligning technical outputs with business priorities.

Documented analytical workflows, SQL queries, and reporting processes, while also delivering ad-hoc analysis and executive-level summaries in Excel, improving transparency, reducing onboarding time, and enabling leadership to make timely, data-driven decisions.

Collaborated in cross-functional meetings with business, risk, and compliance stakeholders, ensuring that analytics deliverables aligned with organizational objectives and regulatory requirements. Environment: Python, R, SQL, Power BI, Excel, VBA, AWS, PostgreSQL, JIRA, Git, SSIS, Power Query, DAX Data Analyst Infosys, India Sep 2021 – Jul 2023

Client: Westpac Banking Corp

Description: Westpac Banking Corporation is one of Australia's major banks providing comprehensive banking and financial services. Responsible for data analysis, business intelligence, statistical analysis, financial analysis, and supporting data-driven decision making across multiple business units including retail banking, commercial banking, and wealth management.

Designed and maintained ETL pipelines with SSIS and Azure data factory, automating data integration from multiple sources and reducing refresh cycles by 30%.

Developed Power BI and Tableau dashboards for loan portfolios and credit risk monitoring, helping managers identify high-risk accounts and lowering non-performing loans by 12%.

Enhanced fraud detection models with SQL anomaly checks and predictive techniques, cutting false positives by 20% and improving detection accuracy.

Utilized SAS and SQL for statistical modeling and regulatory reporting, improving accuracy and meeting compliance deadlines.

Conducted customer behavior analysis using Python and SQL, uncovering spending trends that informed product strategies and improved satisfaction by 18%.

Standardized KPIs, data governance practices, and report templates, increasing data accuracy by 25% and ensuring consistency across business units.

Optimized SQL queries and stored procedures to accelerate reporting, reducing execution time by 40% and improving analyst efficiency.

Built customer churn prediction reports with regression and statistical modeling, enabling proactive outreach that reduced attrition by 15%.

Supported regulatory compliance reporting (Basel III) by preparing audit-ready datasets, collaborating with QA and audit teams to validate data accuracy, and ensuring timely submissions. Environment: SQL Server, SSIS, Azure data factory, Tableau, Power BI, Python, R, SAS, Excel, VBA, Azure cloud, JIRA, Confluence, PowerShell

Education

Master of Science in Computer & Information Science University of Texas at Arlington, TX - USA Bachelor of Technology in Computer Science Dhanekula Institute of Engineering & Technology, AP - INDIA

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