Power Bi Data Analytics

SHIVARAMAKRISHNA KASIREDDY

Baltimore, MD, USA

• +1-443-***-**** • **********************@*****.*** • linkedin.com/in/shivakasireddy SUMMARY

I’m Graduate student in Data Science with over 4+ years of experience in designing and implementing scalable, large-scale distributed systems. Proficient in data modeling, ETL processes, and database management. Experienced in Python development and AI/ML solutions for predictive analytics. Seeking opportunities that emphasize innovation, collaboration, and continuous learning EDUCATION

Master’s in Data Science, University of Maryland Baltimore County, Maryland, US Aug 2022 – May 2024 Bachelor’s in Computer Science, Jawaharlal Nehru Technological University, Telangana, IN Aug 2017 – Aug 2021 TECHNICAL SKILLS

Programming Languages: Python, Java, JavaScript, R, Scala Data Analytics: Tableau, Power BI, R, Pandas, NumPy, TensorFlow, Matplotlib, SciPy, Excel, PowerPoint, Seaborn Data Visualization: Tableau, Power BI, and Plotly

Data Engineering: Apache NiFi, Google Big Query, Apache Airflow, Apache Spark, AWS Lambda, AWS Glue Big data: Hadoop HDFS, Apache Kafka, Hive, Pig, AWS Kinesis Statistical Analysis and ETL Tools : SAS, SPSS, STATA, SSIS, Alteryx, Talend Databases: MySQL, MongoDB, GraphQL, SQL, Oracle MySQL, PostgreSQL, MongoDB, and Cassandra. DevOps: Jenkins, GitLab CI/CD, Docker, Kubernetes, Terraform, Ansible, ELK Stack Cloud Technologies: AWS, Microsoft Azure, GCP

PROFESSIONAL EXPERIENCE

University of Maryland, Baltimore County, USA: Graduate Research Assistant Jun 2023 - Mar 2024

• Optimized SQL queries using MySQL, MSSQL, PostgreSQL, Hive, and Redshift, enhancing data accuracy and efficiency. Utilized Python libraries such as Pandas and Numpy for ETL processes and data analysis.

• Created actionable insights through visualizations using Matplotlib and Seaborn.

• Implemented analytics and visualization solutions with R, Tableau, PowerBI, and Mode Analytics, delivering interactive dashboards and comprehensive reports to stakeholders.

LTIMindtree Limited, Bangalore, India: Data Engineer. July 2021 – Aug 2022

• Implemented distributed data processing solutions using HDFS and Spark, improving data processing speed by 30%.

• Designed and operated NoSQL databases such as Cassandra and Elasticsearch, ensuring 99.9% uptime and high data integrity across large-scale systems.

• Architected and deployed scalable, reliable, and secure distributed data systems using microservices, service mesh, Docker, Kubernetes, and OpenShift, enhancing overall system flexibility and performance.

• Implemented robust data integration solutions using Python, SQL, and ETL tools such as SSIS and Alteryx, resulting in improved data accuracy and reduced processing time.

Sudheeksha Software Solutions Private Ltd., Hyderabad, India: Analyst Sep 2019 –Feb 2021

• Automated manual workflows, achieving a 40% reduction in operational costs by collaborating with business managers.

• Analyzed and cleaned large datasets using SQL, Python, and R, and developed ETL pipelines with Hadoop, Spark, and Hive for data integration.

• Created reports and dashboards with Tableau, PowerBI, and Python libraries (Matplotlib, Plotly, Seaborn) to communicate insights ACADEMIC PROJECTS

Price Performance Prediction Spring 2024

• Developed a dynamic web application using Streamlit for price performance prediction with machine learning (LSTM, GRU, Random Forest) and time series analysis (ARIMA, SARIMA, Prophet). Utilized hyperparameter tuning, advanced data analysis to forecast future price movements.

• Reduced feature dimensionality using Principal Component Analysis (PCA), maintaining 99% of variance with reduced features, significantly speeding up the classification process without sacrificing accuracy. Efficient Inventory Management System (EIMS) via Serverless Architecture Fall 2023

• Implemented the EIMS using Kafka, AWS Lambda, API Gateway, and DynamoDB to provide scalable serverless solutions, enhancing operational efficiency and reducing costs.

• Innovated a real-time inventory management system with advanced performance analytics, utilizing the flexibility of AWS serverless technologies.

Music Recommendation System, Python, Recommendation Systems, Machine Learning Spring 2023

• Led the development of a recommendation system using collaborative/content-based filtering techniques, achieving a recommendation accuracy of 87%.

CERTIFICATION AND AWARDS

Cloud: AWS Solutions Architect Certification, Google Professional Data Engineer, Azure Data Engineer Associate Analytics: Google Data Analytics Professional Certificate

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