Machine Learning Computer Science

NAVYASRI KADIYALA

Lawrence, KS, ***** * : *****************@*****.*** ) : +1-913-***-**** LinkedIn

PROFESSIONAL SUMMARY

•Ambitious Computer Science graduate seeking a full-time role in data analysis, dedicated to leveraging analytical and technical expertise to extract actionable insights and optimize business outcomes.

•Proficient in Python, SQL, and cloud technologies, with experience in creating impactful visualizations and driving data-driven decision-making through collaboration with cross-functional teams.

•Skilled in transforming complex datasets into clear, actionable strategies, solving challenges, and delivering innovative solutions to enhance operational efficiency.

•Successfully executed projects, including an Accident Analysis Dashboard for visualizing road safety trends and a Counterfeit IC Detection System integrating machine learning models for fraud detection.

EDUCATION

University of Kansas, Lawrence, KS

Master of Science, Computer Science (Aug 2022- May 2024)

GPA: 3.5/4.0

Lovely Professional University, Punjab, India

Bachelor of Technology, Electronics and Communication Engineering (Aug 2017-Jul 2021)

GPA: 3.1/4.0

WORK EXPERIENCE

Vertocity, India Data Analyst. Feb 2021 - May 2022

•Led the collection, cleaning, and organization of large datasets from various sources like Google Analytics, Shopify, and CRM tools, ensuring a 98% data accuracy rate and improving data availability for analysis, enabling better decision-making across teams.

•Managed the development and maintenance of real-time dashboards and KPI reports using Tableau, Power BI, SQL, and Python, reducing reporting time by 30% and enhancing the speed and accuracy of data-driven decisions.

•Directed exploratory data analysis (EDA) using Python and R, uncovering customer behavior and market trends, leading to a 25% increase in the efficiency of targeted marketing campaigns and improved business strategies.

•Spearheaded A/B testing to optimize e-commerce marketing strategies, contributing to a 15% increase in conversion rates and a 10% improvement in customer retention, while fostering a data-driven culture within the team.

•Collaborated with cross-functional teams to align data insights with business goals, enhancing strategic decision-making and improving cross-team collaboration effectiveness by 40%, ensuring alignment in achieving organizational objectives.

RELEVENT COURSEWORK

•Data Science

•Intro to Machine learning and Advanced Machine Learning

•Data Privacy and Security

•Computer Science

•Bioinformatics

SKILLS

•Operating Systems: Windows, Ubuntu, Linux

•Databases: Oracle, MySQL, NoSQL, MongoDB

•Programming Languages: Python, SQL, C, C++, C#, HTML5, CSS, Java, JavaScript, React

•Data Analysis Tools: Microsoft Excel, Microsoft Power BI, Tableau, CRM tools, Outlook, PowerPoint

•Frameworks and Libraries: .NET, Scikit-learn, PyTorch, TensorFlow, Cloud Technologies (AWS)

•Development Tools: Microsoft Visual Studio, PyCharm, Postman API, IntelliJ IDEA, Eclipse, GIT, ETL processes

•Data Analytics Expertise: Proficient in data wrangling, Statistics modeling, and predictive analytics with experience in SQL queries and

data visualization platforms

CERTIFICATIONS

•AWS Cloud Practitioner (Udemy)

•Career Essentials in Business Analysis (Microsoft and LinkedIn)

•Python Data Structures & Algorithm (Udemy)

PROJECTS

•Counterfeit IC Detection System: Designed a CNN model achieving 94% accuracy for counterfeit IC detection, outperforming AlexNet and VGG16 models using frameworks like PyTorch and OpenCV.

•K-Anonymity Using Randomization and Clustering: Implemented anonymization techniques ensuring privacy in datasets while maintaining usability with metrics-driven validation.

•Accident Analysis Dashboard: Built an interactive dashboard using Excel to analyze road accident data, providing actionable insights through KPI visualizations.

•Parallax Web Development Showcase: Developed a responsive portfolio website with parallax effects, highlighting full-stack data engineering projects and enhancing user engagement.

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