Data Science with 3+ years in Machine Learning & Predictive Analytics
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Experienced IT professional with 3.1 year of dedicated experience specializing in collecting, analyzing, and interpreting intricate datasets. Proficient in Python, machine learning, predictive analytics, statistical modeling, and data visualization. Demonstrated ability to uncover critical insights and emerging trends within data, proficiently create predictive models, and effectively apply data-driven solutions to propel business growth.
Savitribai Phule Pune University
Bachelor of Engineering
January 1, 2015 – January 1, 2019
ValueSoft Info Services
Data Scientist
April 1, 2023 – Present
Bengaluru, Karnataka, India
Advertisement Expenditure Forecasting
May 6, 2026 – Present
Developed a forecasting model to predict advertisement expenditure for a retail company based on historical data of client. This initiative resulted in a substantial 30% surge in ROI through the enhancement of advertising strategy and targeting. Consequently, this project contributed to heightened brand visibility and increased customer acquisition. Employed advanced machine learning tools to meticulously analyze client records, culminating in the creation of a highly accurate ad spending forecasting model.
Customer Churn Prediction in Bank
May 6, 2026 – Present
Developed a machine learning model with 95% accuracy to predict which customers were likely to leave. This model served to predict potential customer churn, enabling strategic interventions such as targeted marketing campaigns and proactive measures to retain high-risk customers for a prominent bank grappling with customer attrition. Meticulously orchestrated data collection and analysis by interfacing with a database, enabling the identification of key patterns essential for predicting customer churn. Took ownership of the end-to-end machine learning model development process, encompassing data processing, cleansing, robust model training, and meticulous validation.
Insurance Product Review Sentiment Analysis
May 6, 2026 – Present
Performed advanced Sentiment Analysis in focusing on auto insurance customer reviews. Transformed qualitative reviews into quantitative data, applying rigorous preprocessing techniques. Leveraged machine learning algorithms to classify sentiments into positive, negative, or neutral categories. Analyzed the outcomes to derive actionable insights. Employed rigorous preprocessing techniques to transform textual reviews into numerical representations, ensuring data accuracy.
Cultural Fit Analysis
The psychometric test score of 0 provides no positive data points regarding the candidate's cultural fit. Therefore, an assessment of cultural fit based on the provided data is not possible.
Soft Skills & Operational Fit
Based on the provided psychometric test score of 0, there is no assessed indication of soft skills, work attitude, stress handling, or team collaboration. While the resume mentions collaboration and communication, these are self-reported and not validated by assessment data.