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Data Analyst with less than a year in Machine Learning & EDA
Maddirala Gowri Maheswar Reddy is an aspiring Data Analyst with 0.8 years of experience in data analysis, machine learning, and business intelligence. She has successfully worked on projects like sales forecasting, AQI prediction, and retail sales analysis using Python, Pandas, Seaborn, and Power BI. Her skills include data cleaning, feature engineering, model training, and developing interactive dashboards, demonstrating a strong foundation in data-driven decision-making.
Lovely Professional University
Computer Science and Engineering · Computer Science and Engineering
August 1, 2022 – Present
Sri Chaitanya Junior College
Intermediate with Science · Science
April 1, 2020 – March 1, 2022
Jeevana Jyothi High School
Matriculation
April 1, 2019 – March 1, 2020
Blinkit Sales Forecasting Model
February 1, 2025 – March 1, 2025
Analyzed historical sales data to identify patterns in demand, pricing impact, and seasonal fluctuations. Engineered features and trained regression models to accurately forecast future sales. Extracted actionable insights to support strategic decisions in stock management. Achieved an R² score of 0.93, helping improve inventory planning and boost operational efficiency.
View ProjectAQI Prediction
January 1, 2025 – February 1, 2025
Developed a machine learning model to predict Air Quality Index (AQI) based on pollution and weather data. Engineered relevant features like pollutant concentrations and seasonal variables to enhance prediction accuracy. Generated insights to support proactive pollution control and environmental policy decisions.
View ProjectEDA on Amazon Retail Sales
November 1, 2024 – December 1, 2024
Conducted an in-depth Exploratory Data Analysis (EDA) on Amazon sales dataset, identifying key sales trends, customer preferences and inventory patterns. Utilized various statistical and visualization techniques to extract actionable business insights, demonstrating a proactive approach to solving retail challenges. Queried and analyzed structured datasets using SQL for extracting sales trends and customer behavior patterns. Designed and interpreted correlation heatmaps, time series plots, and category-wise sales breakdowns to uncover seasonal effects and high-performing product segments.
View ProjectHealthcare Analytics Dashboard
August 1, 2024 – September 1, 2024
Developed an interactive Power BI dashboard for a hospital management system, providing comprehensive insights into patient visits, staff distribution, treatment costs, ER efficiency, and feedback analysis. Used Power Query Editor to clean and transform data for accuracy and consistency. Designed an effective data model integrating multiple tables (patients, staff, departments, beds) to establish clear relationships and enable detailed drill-downs and slicers for segmented analysis. Implemented key performance indicators (KPIs) for real-time monitoring of patient volume, ER time, bed occupancy, and patient-staff ratio, aiding hospital administrators in data-driven decision-making.
View ProjectData Science using Python
Cipher Schools
November 1, 2024 – Present
Data Science & ML
Upgrad
August 1, 2023 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a breadth of application areas (retail, environmental, healthcare), indicating adaptability and a willingness to explore diverse datasets. The focus on personal projects suggests self-motivation and initiative. The listed certifications further support a commitment to continuous learning. However, without team-based project experience, assessing collaboration and interpersonal skills for cultural fit is challenging.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and a focus on delivering actionable insights, which are positive indicators for operational fit. The emphasis on achieving specific results (e.g., R² score of 0.93) suggests a results-oriented mindset. However, without direct work experience or psychometric test results, it's difficult to fully assess soft skills like teamwork, communication in a professional setting, or stress handling.