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Data Science with less than a year in sales forecasting, AQI prediction, and retail data analysis.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
An aspiring Data Scientist with hands-on experience in developing machine learning models for predictive analytics, performing in-depth exploratory data analysis, and creating interactive dashboards. Proficient in Python, SQL, and various data manipulation and visualization libraries, seeking to leverage analytical skills to drive data-driven decision-making.
Lovely Professional University
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 project portfolio demonstrates a breadth of application areas within data science, including retail sales, environmental monitoring, and healthcare analytics. This diversity suggests adaptability and a willingness to tackle different types of data challenges. The focus on personal projects indicates self-motivation and a passion for the field. The skills listed (Python, SQL, ML, Power BI) are highly relevant to a Data Science role, indicating a good technical fit. However, the lack of professional experience means cultural fit related to workplace dynamics and collaboration in a professional setting cannot be fully assessed.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and a focus on extracting actionable insights, which suggests good analytical thinking and a results-oriented mindset. The detailed descriptions of methodologies and outcomes (e.g., R² score, KPI implementation) reflect an ability to articulate technical work clearly. However, without direct interaction or psychometric test results, assessing stress handling, team collaboration, and work attitude is not possible.