Data Analyst Science

Mounika Poreddi

Data Analyst Business Analyst

• 443-***-**** • *********@****.*** • linkedin.com/in/mounika-poreddi/

EDUCATION

University of Maryland, Baltimore County (UMBC)

Master of Professional Studies, Data Science GPA: 3.89

SKILLS

Cloud & Big Data Platforms:

Azure, Data Bricks, Snowflake, Apache Spark, Hadoop

Programming & Data Science:

Python (NumPy, Pandas, Matplotlib, Scikit-Learn), Machine Learning, NLP, Time Series Forecasting, ARIMA, Linear Regression, Big Data Management, ETL, Data Warehousing, Apache Spark, Hadoop, Data Bricks, Snowflake

Databases:

SQL (MS SQL, Oracle SQL, PostgreSQL, Azure SQL, PL/SQL), Chroma DB

Data Engineering & Data Modeling:

Data Modeling (Star & Snowflake Schema), Data Warehousing & ETL (Extract, Transform, Load), Google Big Query & Google Cloud Platform (GCP), SQL Performance Tuning & Query Optimization, Data Validation & Quality Assurance, Data Governance & Compliance

Data Analysis & Visualization Tools:

Microsoft Excel (Pivot Tables, Power Query, VLOOKUP, Data Analytics), Power BI (DAX, Data Transformation, Report Designing), Tableau, Dashboard Development (Tableau, Looker), Advanced SQL (CTEs, Window Functions, Analytic Functions), Business Intelligence & Reporting

Additional Skills:

C#, ASP.NET Core, Entity Framework, Data Structures, Algorithms, Web API, Stakeholder Engagement & Cross-functional Collaboration, Translating Business Requirements into Data Solutions, Agile & Scrum Methodologies

EXPERIENCE

Cloudleap Technologies – Data Science Intern Jan 2024 – Present

Developing AI-driven solutions using Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and Vector Databases for federal government contracting.

Fine-tuning pre-trained models and implementing vector search using Chroma DB to enhance document retrieval and summarization.

Collaborating with stakeholders to develop AI pipelines optimizing data extraction, document processing, and decision support.

Student Advising UMBC – Data Analyst Intern Sept 2023 – Aug 2024

Analyzed over 5,400 student feedback responses, identifying trends that increased student satisfaction by 12%.

Utilized Python (Pandas, Matplotlib) to visualize satisfaction metrics across 12 key service areas, generating weekly reports.

Designed and deployed interactive Power BI dashboards, empowering 35+ department heads to make real-time, data-driven decisions.

Presented findings in a final report, leading to 15% higher engagement and 10% improvement in service quality.

Infosys - Data Analyst Bangalore, KA Sept 2021 - Jan 2023

Migrated legacy codebase to ASP.NET Core, optimizing application scalability and transitioning data to Azure SQL Server.

Conducted data analysis using Python (NumPy, Pandas, Matplotlib) to derive business insights from large datasets.

Developed interactive dashboards in Power BI, Tableau, and Excel, supporting data-driven decision-making.

Collaborated with cross-functional teams to integrate analytics solutions, enhancing application functionality and user experience.

PROJECTS

Strategic Portfolio Optimization and Forecasting Python, ARIMA, CAPM, Matplotlib

●Designed a comprehensive portfolio analysis framework utilizing the yahoo finance library to import historical stock data from Yahoo Finance.

●Developed CAPM models to calculate expected returns and constructed correlation matrices for diversification assessment across various industries, including technology, healthcare, and energy.

●Conducted statistical analyses with ADF tests for stationarity and ACF/PACF analysis to evaluate stock data properties.

●Built forecasting models using ARIMA, AR, and MA techniques to predict future stock prices, aiding in strategic portfolio allocation.

●Created interactive visualizations with Matplotlib, Seaborn to illustrate portfolio performance and optimized allocation strategies, benchmarking against the S&P 500 index.

Road Crash Analysis and Severity Prediction Python, Machine Learning

●Conducted a comprehensive analysis of road crash data in Baltimore County to develop predictive models for accident severity using Linear Regression, Random Forest, and Decision Tree algorithms.

●Employed advanced data analysis techniques, including a correlation matrix, to identify key factors influencing crash outcomes and enhance understanding of contributing variables.

●Created impactful visualizations to effectively communicate findings and support data-driven recommendations for improving road safety and informing local policy decisions.

Taxi Availability Prediction Python, Data Analysis, Machine Learning

●Developed a predictive model to forecast taxi availability in New York City using historical ride data and machine learning algorithms, enhancing operational efficiency for taxi services.

●Conducted thorough data analysis to identify patterns and trends in ride demand, incorporating factors such as time of day, weather conditions, and geographic hotspots.

●Implemented visualizations to present insights and recommendations for optimizing fleet distribution and improving service levels based on predicted demand.

CERTIFICATIONS

●Microsoft and LinkedIn certified Data Analyst (Excel, SQL, Power BI)

●Microsoft SQL Server (Aug 2021)

●ASP.NET Web API (Sept 2021)

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