LASYA KONDURU

Results-driven data professional with a strong foundation in data analysis, machine learning, and statistical modeling. Proficient in Python, R, SQL, and Tableau, with hands-on experience in developing data-driven solutions and creating interactive visualizations. Adept at leveraging data to extract actionable insights, optimize processes, and support decision-making. Skilled in building and validating predictive models, data cleaning, and wrangling. Strong analytical and problem-solving abilities, with a passion for turning complex datasets into meaningful business insights. Excellent communicator, eager to apply technical expertise in a dynamic environment.

Enhancing Sales Performance and Operational Efficiency in a Superstore Using AWS Athena and QuickSight
06/2024

• Utilized AWS Athena for efficient data querying and AWS QuickSight for data visualization to analyze and optimize sales performance.
• Conducted in-depth customer segmentation, shipping logistics analysis, and discount impact studies, leading to a 15% increase in sales and a 20% reduction in operational costs.
• Developed and deployed interactive dashboards to support data-driven decision-making across various business units.

Steel-Manufacturing Analysis
01/2024 - 03/2024

• Compared and evaluated multiple predictive models using performance measures and computational time optimization.
• Achieved a 30% improvement in predictive accuracy and a 25% reduction in computation time, enhancing decision-making processes related to sales funnel optimization.
• Provided actionable insights to improve customer conversion rates and sales strategies using data-driven analysis.

Breast Cancer Analysis
04/2024

• Developed a machine learning model utilizing real-valued characteristics from breast mass cell nuclei to distinguish between benign and malignant tumors.
• Enhanced diagnostic accuracy by 35%, facilitating earlier detection and more precise treatment options for patients.
• Conducted data preprocessing, feature selection, and model validation to ensure clinical robustness and interpretability.

Prediction of Crop Yield
01/2022 - 07/2022

• Created a machine learning-based web platform for crop yield prediction, integrating meteorological, soil, and agricultural data for accurate yield estimates.
• Improved prediction accuracy by 40%, resulting in a 25% increase in agricultural profitability and optimized crop selection for farmers.
• Employed data integration and model optimization techniques to provide real-time recommendations, boosting agricultural productivity.

BCG Data Science Job Simulation | Forage
September 2024

• Conducted customer churn analysis using Python, leveraging Pandas and NumPy for data manipulation and trend analysis.
• Engineered and optimized a Random Forest model with an 85% accuracy in predicting churn, providing actionable insights through a strategic investigation approach.
• Delivered a concise executive summary to the Associate Director, driving data-driven decision-making.

British Airways Data Science Job Simulation | Forage
September 2024

• Analyzed customer review data through web scraping to identify key insights.
• Developed a predictive model to identify factors influencing buying behavior, enhancing business strategies with data-driven insights.
• Demonstrated the impact of data science on operational success through clear and concise analysis.

• AWS Certified Data Analytics — Specialty [03/2024 - 03/2027] Amazon Web Services
• R for Data Science: Analysis and Visualization [10/2023] - LinkedIn
• SQL Essential Training [06/2023] - LinkedIn
• Excel: Economic Analysis and Data Analytics [06/2023] - LinkedIn
• Data Science Methodologies [10/2022] - IBM