Machine Learning Data Science

LAXMIKANTH REDDY JITTA

203-***-**** ************@*****.*** LinkedIn Portfolio New Haven, CT

Education

Master of Science in Data Science - Sacred Heart University - Fairfield, CT August 2023 - December 2024

Bachelor of Technology in Mechanical - JNTUH - Hyderabad, Telangana June 2019 - August 2022

Skills

Programming Languages: Python, R, SQL, Java

Data Tools: Power BI, Tableau, SAS, Excel, Power Point, SharePoint, AWS

Libraries/Frameworks: Pandas, NumPy, SciPy, Matplotlib, Seaborn, statsmodels, scikit-learn, TensorFlow, PyTorch, Cucumber, Selenium

Soft Skills: Detail-oriented, Strong Communication (written and verbal), Collaborative, Agile Methodologies, Adaptability, Problem-Solving, Time Management, Multitasking, Attention to Detail, Interpersonal Skills, Critical Thinking

Additional Expertise: Data Analysis, Statistical Analysis, Data Modeling, Machine Learning, Data Visualization, Linear Regression, Decision Trees, Data Mining, Data Warehousing, ETL, ELT, Natural Language Processing, Neural Networks, Computer Vision, Git, GitHub, AutoCAD, SolidWorks, Ansys

Work Experience

ShrimpIQ September 2023 – March 2024

Machine Learning Intern Naperville, IL

● Developed and deployed a real time shrimp quality control system using the YOLO object detection model.

● Performed data preprocessing, data modeling, and analysis to prepare training datasets, improving model accuracy and robustness.

● Computerized the detection of improperly peeled shrimps, reducing manual inspection efforts by 80% and improving defect identification.

● Fine-tuned the model through experimentation, analyzed numerical data, and validated results to optimize defect detection, increasing production efficiency by 15%.

● Integrated machine learning with existing work flows, leading to a 10% reduction in production downtime and improved KPI tracking for defect rates and production quality.

Cognizant Technology Solutions February 2022 - June 2023

Programmer Analyst Hyderabad, India

● Played a key role in enhancing software applications robustness and reliability through systematized data driven testing processes.

● Developed and Maintained automated test scripts using Java and Selenium, resulting in a 30% reduction in manual testing efforts.

● Systematically reviewing processes and validating software performance through detailed reporting.

● Analyzed and reported performance metrics, providing actionable insights to the development team for code optimization.

● Utilized Jira for defect tracking, facilitating data-driven communication between development and testing teams.

● Generated comprehensive reports, summarizing experimental results, statistical analyses, and process validation findings to support data-driven decision-making.

Projects

Energy Consumption Analysis

●Used Python to analyze energy consumption across various regions over different time periods.

●Exploratory Data Analysis Is performed to identify the patterns, trends and correlations in the data.

●Aggregated and visualized the data by using pandas, matplotlib to gain insights and improve understanding.

●Applied Random Forest model to predict the future energy consumption based on the data, achieving a prediction accuracy of 90%.

Sentiment and Temporal Analysis

●Scraped and analyzed posts about the ChatGPT from subreddit to understand sentiment trends using VADER, TextBlob and other similar tools.

●Preprocessed text data with Natural Language Processing techniques and regular expressions to clean and prepare it for analysis.

●Generated word clouds to visualize frequently mentioned terms in the posts, providing insight into user discussions.

●Analyzed temporal dynamics of user engagement, correlating sentiment with metrics like upvote ratios and post scores.

Car Sales Analysis

●Extracted and prepared data from related tables in car sales databases using SQL JOIN and VIEW.

●Processed and cleaned data using Python libraries like Pandas, Seaborn for accurate analysis and visualization.

●Conducted Exploratory Data Analysis to identify trends, correlations, and data patterns for model insights.

●Developed a regression model to predict car prices based on features such as mileage, age, and brand, achieving 85% accuracy.

Certifications

●Google Data Analytics Professional Certificate

●Microsoft Certified: Power BI Data Analyst Associate

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