Data Analyst Visualization

Munireddygari Latha Pravalika Data Analyst

*************@***********.*** 314-***-**** USA LinkedIn

Summary

Results-driven Data Analyst with 2+ years of experience transforming complex data into actionable insights to support strategic business

decisions. Skilled in SQL, Python, R, and BI tools with a strong foundation in data wrangling, statistical analysis, and data visualization.

Proficient in building automated ETL pipelines using cloud platforms like AWS and Azure. Known for improving data accuracy, optimizing

workflows, and delivering interactive dashboards that enhance decision-making. Adaptable, collaborative, and committed to driving data-

informed solutions across cross-functional teams.

Technical Skills

• Data Analysis & Statistical Modeling: Python (NumPy, Pandas, Matplotlib), R, Value at Risk (VaR), Monte Carlo Simulations, Standard

Deviation, Beta Coefficient, K-Means Clustering, Time Series Forecasting

• Data Querying & Databases: SQL (JOIN, GROUP BY, HAVING, Window Functions, Subqueries), AWS Athena, SAP, Oracle

• ETL & Data Integration: AWS Glue, AWS S3 (CSV), Azure Data Factory, Automated ETL Pipelines, Data Validation

• Data Visualization & Reporting: Power BI (DAX, Drill-through, Trend Analysis), Tableau (LOD Calculations, Dynamic Filters)

• Cloud Platforms: Amazon Web Services (AWS), Microsoft Azure

• Tools & Platforms: CRM, ERP Systems, Agile Methodologies (Scrum)

Professional Experience

Data Analyst, Ameriprise Financial 08/2024 – Present Remote, USA

• Worked on Risk Analysis for Financial Products, collaborating with the Risk Management, Product, and IT teams in Agile sprints. Led

requirement gathering sessions to assess risk profiles of products like mutual funds, insurance policies, and retirement plans.

• Utilized SQL methods like Window Functions and Subqueries to query large financial datasets, optimizing query performance by 25%.

Employed AWS Athena for ETL, extracting data from S3 buckets (CSV format) for analysis of risk data.

• Conducted Value at Risk (VaR) analysis and Monte Carlo simulations on investment products, including mutual funds and insurance

policies, to quantify the risk and potential return under different market conditions. Identified a 15% potential risk reduction.

• Used Python (NumPy, Pandas) along with Statistical Analysis (e.g., Standard Deviation) and Risk Metrics (e.g., beta coefficient) to

process financial data. Improved risk modeling accuracy by 20%, leading to better product risk assessment for clients.

• Performed data validation and automated ETL pipelines using AWS Glue and AWS Athena to ensure data integrity. Reduced data errors

by 10% and increased the speed of processing financial product data by 30%.

• Developed Power BI dashboards with dynamic filters, trend analysis, and drill-through functionality. Used DAX to calculate risk-adjusted

returns and visualize performance trends, leading to a 25% increase in report generation efficiency.

Associate Data Analyst, Logitech 07/2021 – 07/2023 Tamil Nadu, India

• Collected sales data from multiple systems (CRM, ERP), collaborating with Sales, Marketing, and IT teams in Agile sprints. Led

requirement gathering sessions to align stakeholders, resulting in a 25% reduction in reporting discrepancies.

• Utilized SQL methods such as JOIN, GROUP BY, and HAVING for querying large sales datasets, optimizing query performance by 20%.

Implemented ETL workflows using Azure Data Factory to streamline data integration from SAP and Oracle databases.

• Conducted trend analysis using time series forecasting to identify seasonal patterns and revenue fluctuations. Discovered a 15%

increase in sales during Q4, enabling the team to adjust marketing strategies accordingly.

• Utilized Python with NumPy, Pandas, and Matplotlib for data processing and exploratory analysis. Improved data transformation

processes, reducing time for monthly sales reports by 30% and enabling faster decision-making.

• Applied K-means clustering in R to segment customers based on purchase behaviors, identifying key customer segments. This

segmentation improved marketing targeting, resulting in a 12% increase in conversion rates for targeted campaigns.

• Performed data validation within Azure Data Factory to ensure data integrity, eliminating errors in sales data reporting. Automated ETL

pipelines, resulting in a 10% reduction in manual data cleaning tasks.

• Developed interactive Tableau dashboards with dynamic filters and trend lines, utilizing Level of Detail (LOD) calculations to analyze

sales performance at regional levels. The dashboards improved executive decision-making by 20%.

Education

Webster University St. Louis, Missouri, USA

Master of Science in Information Technology Management 08/2023 – 03/2025

SASTRA University Thanjavur, Tamil Nadu, India

Bachelor of Business Administration & Bachelor of Laws (BBA, LLB) 07/2017 – 08/2022

Contact this candidate