Summary
Overview
Work History
Education
Skills
Certification
Projects
Timeline
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Yagna Sree Inturi

Summary

DATA ANALYST

Welcome to my Portfolio! This is Yagna Sree Inturi. I am a dedicated Data Analyst with a strong proficiency in SQL, Python, and data visualization tools such as Tableau and Power BI. I specialize in leveraging advanced data analysis techniques and statistical models to drive informed decision-making and operational efficiency.

I am committed to staying at the forefront of data analytics, continually enhancing my skills in machine learning and predictive analytics. My expertise in managing large datasets and implementing ETL processes ensures high data quality and reliability. With experience in cloud platforms like AWS and Azure, I deliver scalable and robust data solutions.

As a proactive team player, I excel in collaborative environments and am adept at translating complex data insights into actionable business strategies. I am driven by a passion for using data to uncover trends, solve problems, and contribute to business innovation and success.

Overview

5
5
years of professional experience
2
2

Certifications

Work History

Data Analyst

Tungsten Automation
USA
04.2023 - Current
  • Analyzed and interpreted complex data sets using SQL and Python, leading to the development of weekly, monthly, and quarterly reports that tracked key performance indicators (KPIs) for 5+ major projects, influencing strategic decisions across the company
  • Employed statistical techniques and machine learning models to predict trends and behaviors across operational data, enhancing predictive accuracy by 35% and supporting proactive business strategies
  • Created and maintained over 30 dynamic dashboards and visualizations using Tableau and Power BI, providing actionable insights that improved decision-making processes and enhanced operational efficiency by 20%
  • Conducted comprehensive analysis of operational processes using agile methodologies, identifying and implementing improvements that resulted in a 25% increase in process efficiency and a reduction in costs by $100K annually
  • Directed and analyzed big data using Hadoop ecosystems, processing approximately 2 TB of data weekly, which facilitated detailed analytics and supported data-driven decision-making
  • Oversaw the maintenance and updating of data systems using Oracle and MySQL, ensuring high data quality and reliability with a 98% uptime and supporting user access for over 500 employees
  • Collaborated with engineering, marketing, and finance teams to integrate new analytical methods and tools, increasing data usability by 40% and enhancing cross-departmental data integration
  • Implemented rigorous data validation processes that reduced data discrepancies by 50%, ensuring the integrity and accuracy of reports used by senior management for critical business decisions
  • Led training sessions on data analytics tools and best practices for 50+ staff members, increasing the analytics capabilities of the team by 30% and fostering a data-driven culture within the organization
  • Ensured compliance with GDPR and other relevant data protection laws by establishing strict data security protocols, significantly mitigating legal and compliance risks related to data handling.

Data Analyst

High Radius Technology
India
01.2021 - 07.2022
  • Analyzed over 10 million financial transaction records using SQL and Python, identifying key trends and anomalies that led to a 20% reduction in transaction errors and optimized payment processes
  • Developed 15+ interactive dashboards and reports using Tableau and Power BI, facilitating real-time business decisions and increasing report accessibility for stakeholders by 35%
  • Designed and implemented predictive models using R and Python, improving the accuracy of customer payment behavior predictions by 40%, which significantly enhanced credit risk assessment processes
  • Carried out data mining on large datasets to improve financial forecasting accuracy by 25%, using advanced statistical techniques and tools such as SAS and Excel
  • Automated recurring data extraction, transformation, and loading processes, decreasing manual data handling time by 50% and enhancing data accuracy across all reporting frameworks
  • Collaborated with cross-functional teams to define and refine data requirements, ensuring alignment with strategic objectives and enhancing data utilization in decision-making by 30%
  • Instituted rigorous data quality control measures, maintaining a data accuracy rate of over 98%, which supported compliance with internal standards and external regulations
  • Trained team members on data analytics techniques and tools, fostering a data-driven culture and enhancing team productivity by 15%
  • Headed 5+ large-scale data analytics projects from inception to deployment, ensuring timely delivery within budget and achieving a project success rate of 100%
  • Enforced strict data security protocols and compliance with data protection laws (like GDPR), safeguarding sensitive information and mitigating legal risks.

Data Analyst

Magna Infotech
India
05.2019 - 12.2020
  • Engaged in comprehensive data analysis projects at Magna Infotech, employing statistical techniques and data modeling tools like Python and R to extract actionable insights from large datasets, directly collaborating to enhance business decision-making processes
  • Assisted in the development and optimization of SQL queries and database structures, improving data retrieval efficiency by 15% and supporting key financial and operational reporting needs
  • Collaborated with senior data analysts to implement robust ETL pipelines, ensuring seamless data integration from multiple sources and maintaining high data integrity and timeliness for strategic projects
  • Participated in the creation of dynamic dashboards and visualizations using Power BI and Tableau, providing stakeholders with real-time insights into performance metrics and trends, and facilitating quick and informed business decisions
  • Contributed to team efforts in data quality management, involving data validation and cleaning processes to uphold data accuracy and consistency, reducing data discrepancies by 20% across key business segments.

Education

Master of Applied Science - Computer Science

University of Cincinnati
Cincinnati, OH
04.2024

Skills

  • Languages: Python, R, SQL
  • Tools: Tableau, Power BI, Advanced Excel (Pivot Tables, VLOOKUP)
  • ETL: Informatica, Data Stage, SSIS
  • Libraries and Frameworks: NumPy, SuPy, Doto, Pickle, Pyside, Pylables, Data Frames, Pandas Matplotlib, Flask, Pandas, seaborn, Apache, Kafka, AWS
  • IDE: PyCharm, PyScripter, Spyder, PyStudio, PyDev, IDLE, NetBeans, Sublime Text Visual Code
  • Machine Learning and Analytical Tools: Supervised Learning (Linear Regression Logistic Regression, Decision Tree Random Forest SVM, Classification Unsupervised Learning (Clustering, KNN, Factor Analysis, PCA), Natural Language Processing, Google Analytics Fiddler, Tableau
  • Cloud Computing: AWS, Azure, Rackspace, OpenStack
  • Databases/Servers: MySQL, SQLite3, Cassandra, Redis, PostgreSQL CouchDB, MongoDB, Teradata, Apache Web Server
  • AWS Services: Amazon EC2 Amazon S3 Amazon Simple DB Amazon MQ Amazon ECS, Amazon Lambdas Amazon Sagemaker Amazon RDS, Amazon Elastic Load Balancing Elastic Search, Amazon SQS, AWS Identity and access management
  • Build and Cl tools: Docker, Kubernetes, Maven, Gradle, Jenkins
  • SDLC/Testing Methodologies: Agile/ Scrum, Waterfall, TDD
  • Techniques: Business Needs Analysis, Data Modeling, Analytical Problem Solving, Data Integrity Validation, Database Management, Project Management, Data Mining, Time-series analysis, Git

Certification

  • AZ 204 - Developing Solutions for Microsoft Azure
  • DP 900 - Microsoft Azure Data Fundamentals

Projects

Software Fault Prediction using Feature Selection, (Python (Pandas, NumPy, Matplotlib, Sklearn), Supervised & Unsupervised Learning, Naive Bayes, PSO, Ensemble feature selection, Genetic, Data Mining techniques)

  • Built a robust machine learning model for software fault severity classification using a 36,000-record dataset. Achieved superior multiclass classification results with a focus on system reliability.

Drowsiness Detection Using Image Segmentation (Python, CNN, Pygame, OpenCV, Machine and Deep Learning Algorithms)

  • Employed Deep Learning to monitor driver alertness in real time, achieving a 90% efficiency boost. Implemented timely alerts for drowsiness detection.

Timeline

Data Analyst

Tungsten Automation
04.2023 - Current

Data Analyst

High Radius Technology
01.2021 - 07.2022

Data Analyst

Magna Infotech
05.2019 - 12.2020

Master of Applied Science - Computer Science

University of Cincinnati

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Yagna Sree Inturi