NOYAL JONNALAGADDA

Dallas, TX (***)- *** **** ad1b6j@r.postjobfree.com

https://www.linkedin.com/in/noyal-jonnalagadda

https://github.com/noyal727

EDUCATION G.P. A: 3.625

The University of Texas at Dallas Dallas, TX

Master of Science in Business Analytics August 2022 Dean’s Excellence Scholarship.

SRM University G.P.A: 3.6

Bachelor of Technology in Computer Science & Engineering. Amaravati, India Dean’s Excellence Scholarship.

Technical Skills

Programming Languages: JAVA, R, SAS, PYTHON, SQL

Visualization: TABLEAU, R, SAS

Front End: HTML, JAVASCRIPT, CSS

Data Bases: MySQL, MongoDB

Cloud Technologies: AWS, GCP, HADOOP, SPARK, FLUME, SQOOP, IMPALA EXPERIENCE

Quinbay Private Limited Bengaluru, India

Data Analyst Engineer August 2021 – April 2022

• Orchestrated the development of web applications using Java, Angular-JS, HTML/CSS, and MongoDB.

• Led an insightful exploration into 5-year product trends for 50K SKUs, utilizing ML models to propel monthly revenue by

$10,000.

• Engineered Java web crawling scripts, radically reducing competitor data crawling time by 50%.

• Strategically managed and meticulously mapped competitor data with the company's website data.

• Fostered high-quality software in an agile environment and constructed Tableau dashboards for in-depth performance analysis. Quinbay Private Limited Bengaluru, India

Software Development Engineer Intern February 2021 – August 2021

• Mastered the art of developing a software application using HTML5, CSS3, Spring Boot, MongoDB, and Vue JavaScript frameworks.

• Developed a web-based application similar to Facebook in just four days. ACADEMIC PROJECT

Engineered and Evaluated Machine-Learning Models to Decipher Customer's Purchasing Behavior

• Developed a statistical Machine learning models of Poisson, Negative Binomial Distribution’s and Poisson regression, NBD regression over customers purchasing data with the estimated parameters and the maximum value of the log-likelihood.

• Compared the models using Bayesian Information Criteria and Akaike's Information Criteria to determine the best-performing model.

Spearheaded Data Processing, Analysis, and Visualization Leveraging Hadoop Tools and Techniques

• Used truck fleet data to refine and analyze trucking movement to meet the organizational goal of better understanding risk, objective is identifying dangerous commercial truck drivers nationwide.

• Loaded data into HDFS, created necessary HIVE tables, and integrated HDFS with Tableau via JDBC drivers for Impala and Hive.

• Conducted data analysis and created stories and visualization maps on Tableau. Crafted Sleep Classification Models and Predicted Sleep Stages Using Python and Machine Learning

• Data is pre-processed to get the features for modelling and training the machine algorithms as data derived from the device is raw and not understandable to train the model. Features derived after pre-processing the data are Motion, Heartrate and Labelled sleep stages.

• Trained the data with various ML- algorithms and calculated the accuracy of each model to understand the better model.

• Further Classified sleep into good, moderate, and bad using processed data to derive useful features for sleep classification.

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