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Data Analyst Analysis

Location:
Garland, TX
Posted:
September 29, 2023

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Resume:

PRANAV NARESH MEDHI

Dallas, Texas adz1va@r.postjobfree.com 682-***-**** pranav-medhi pranavmedhi123 EDUCATION

Master of Science in Computer Science The University of Texas at Arlington CGPA 3.63/4 May’2021 Relevant Courses: Data Mining, Big Data, Cloud Computing, Database Systems, Data Analysis and Algorithms, Neural Networks, Web Data Management, Artificial Intelligence, Computer Vision, Machine Learning. PROFESSIONAL EXPERIENCE

Technology Analyst August’21 – July’23

Goldman Sachs via Infosys, Dallas

• Preprocessed and analysed transaction data of metrics 10GB using Python, Excel. Collaborated seamlessly across diverse financial domains including treasury management, Foreign Exchange, Fixed Income Currency and Commodities, Credit.

• Communicated insights and suggestions highlighting risks to stakeholders by comparing and analysing the data reports using technologies such as SQL, Tableau, Business Intelligence tools. Resulting sales lift of 28% in just 9 months.

• Designed KPI dashboards in Qlikview for continuous improvement and tracking of findings/trends for forecasting.

• Documented issues faced during batch processing for ETL, data pipelines in a Confluence page, spearheaded resolutions involving automation which resulted in saving hours’ worth of daily efforts, faster processing, monetary value for firm. Research Assistant [Website] June’21 – August’21

The University of Texas at Arlington, Arlington

• Lead a team of 5 in improving and updating features of an existing educational website in the Laravel Framework using PHP, MySQL, CSS technologies. Developed the backend APIs using Node.js, JavaScript.

• Presented and coordinated updates done by teammates using Bitbucket Branching. TECHNICAL SKILLS

• Programming Languages and Skills: Python, SQL, R, Statistics, ETL, UNIX.

• Libraries: Scikit-learn, Regex(re), Pandas, Matplotlib, NumPy, Seaborn, tweepy, Beautiful Soup, statsmodels.api.

• Analytical Tools: Excel, Jupyter Notebook, Confluence, JIRA, QlikView, AWS, Informatica.

• Visualisation Tools: Tableau, Power BI.

ACHIEVEMENTS & CERTIFICATIONS

Udacity Data Analyst NanoDegree Certification, March 2022. [Credential] Improved and Presented on the ‘Abnormality Detection in a Mammogram Using Convolution Neural Network Learning’, paper by Pencheng Xi, IEEE Journal, September 2018. PROJECTS

WeRateDogs Twitter Dataset (Python, Tableau, Tweepy, Regex) [Github] Spring’2022

• Engineered a dataset by capturing 4,356 unique tweets with 17 attributes via the Tweepy API.

• Normalized the dataset and reduced size by 20%, enhancing parameter relation identification.

• Conducted exhaustive data analysis, revealing key insights and correlations.

• Visualized intricate analyses into intuitive Tableau data storytelling, effectively conveying 10 pivotal insights. Exploration of Prosper Loan Data (Python, Jupyter Notebook slides, seaborn) [Github] Spring’ 2022

• Analysed a dataset of Loan data which consisted of 113,937 loan instances and 81 variables.

• Executed 3 methods of exploration, using visualization libraries of Python.

• Communicated 25 findings while highlighting decisive loan acceptance variables for any given individual. Perform A/B Testing for a Website Update (Python, statsmodels.api, matplotlib, Pandas) [Github] Spring’ 2022

• Analysed a dataset of website viewership and timestamps, it comprised of 294,478 instances and 5 variables.

• Performed A/B testing using 3 different methods to analyse the success of the new Webpage. Wisteria Housing Website (PHP, SQL, NodeJS, CSS, HTML, Laravel) [Video Demo][Github] Spring’ 2021

• Migrated a housing website from PHP to Laravel Framework (developed from scratch), Upgraded the website visually.

• Built and integrated an interactive Chat application in the framework, using NodeJS, socket.io, moment.js. Board Game Geek Review Prediction (Keras, Jupyter Notebook, AWS, Flask) [Video Demo][Github] Fall’ 2020

• Implemented and improved upon a Multinomial Naïve-Bayes Classifier Model on this cleaned dataset for estimating the ratings with an accuracy of 90%.



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