Ruchitha Gajawada

Ruchitha Gajawada

Intern

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  • Timeline

  • About me

    Computer Science, M.S. at Lamar University | Full Stack| Data Science | Data Analytics | Machine Learning | Business Analytics | Power BI | Tableau | Python | SQL | Excel | Statistical Analysis

  • Education

    • Lamar University

      2022 - 2024
      Masters Computer Science 3.84/4.00
    • G. Narayanamma Institute Of Technology And Science

      2018 - 2022
      Bachelor of Technology - BTech Electronics and Communication Engineering 3.68/4.00
  • Experience

    • Smart Bridge Solutions Private Limited

      Apr 2019 - Jun 2019
      Intern

      Experienced in IoT, cloud computing, and device integration. Contributed to POC development for smart fishponds and intruder detection using NodeMCU and Raspberry Pi.

    • International School of Engineering (INSOFE)

      Sept 2019 - May 2020
      Data Science Trainee

      Specialized in analytics and machine learning methodologies, gaining practical experience in advanced data analysis techniques and their real-world applications.

    • Discover Financial Services

      Aug 2020 - Jul 2022
      Data Analyst

       Developed a student performance prediction model using Flask & Python, achieving 90% accuracy and improving graduation rates. Built scalable data pipelines for data ingestion, transformation, and model training, improving processing efficiency by 30%. Designed a spam email classifier (97% accuracy, 100% precision) using NLP techniques (NLTK, Naive Bayes), deployed on AWS. Created a movie recommendation system using NLP (Bag of Words, Cosine Similarity), improving user engagement by 15%. Developed interactive Tableau & Power BI dashboards for key performance metrics, increasing data accessibility by 30%. Show less

    • Lamar University

      Sept 2023 - May 2024
      Data Analyst - Teaching Assistant

       Designed and developed AI-driven data analytics pipelines, improving data processing efficiency by 40%. Created machine learning models for predictive analytics, achieving 85%+ accuracy across multiple projects. Supported students in developing data pipelines, model optimization, and hyperparameter tuning using Linear Regression and Random Forest Regressor. Developed and optimized SQL queries, reducing query execution time by 50%. Built and deployed data visualization dashboards using Power BI, increasing accessibility of insights by 30%. Conducted sentiment analysis on real-world datasets, helping businesses improve customer experience by 25%. Show less

    • NBCUniversal

      Jul 2024 - Jan 2025
      Data Analyst

       Developed and deployed predictive models on AWS, improving model accuracy by 20%. Built a 92% accurate predictive model for bank deposit marketing using Python and sci-kit-learn, increasing conversion rates. Applied SHAP values for customer segmentation, reducing unwanted calls by 96% and enhancing marketing efficiency. Optimized machine learning models with hyperparameter tuning & dimensionality reduction, reducing computational costs by 25%. Implemented Random Forests and Gradient Boosting techniques, achieving an average of 90% accuracy across multiple projects. Conducted EDA on structured/unstructured data, uncovering key insights that reduced false negatives by 15%. Show less

  • Licenses & Certifications