Sandip Salunkhe

Sandip Salunkhe

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Pune, Maharashtra, India

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Résumé

Jobs verified_user 0% verified
  • Bajaj Finserv
    DATA SCIENCE INTERN
    Bajaj Finserv
    Aug 2024 - Jan 2025 (6 months)
    • Problem: Addressed the challenge of predicting customer loan defaults to enhance financial stability and risk management • Approach: Collaborated with cross-functional teams to gather and preprocess financial data using Python (Pandas, Numpy). • Used Machine learning frameworks like Scikit-Learn and TensorFlow to develop predictive models. • Solution: Created a predictive model with 90% accuracy, leveraging advanced data analysis techniques to identify high risk customers. • Impact: Enabled proactive risk management, reducing loan defaults by 15% and contributing to cost savings of approximately 20%. Presented findings through comprehensive reports and visualizations to stakeholders.
Education verified_user 0% verified
  • W
    Master's in Computer Science
    Woolf University
    Nov 2024 - Current (1 year 11 months)
  • I
    Bachelor of Engineering (B.E)
    ISB&M College of Engineering
    Jun 2020 - Jun 2024 (4 years 1 month)
Projects (professional or personal) verified_user 0% verified
  • S
    TELECOM CHURN PREDICATION
    Self Owned
    Jan 2024 - May 2024 (5 months)
    • Developed a churn predication model to enhance customer retention in the telecom sector. • Built a telecom churn predictor using Logistic Regression, achieving 89% accuracy. • Conducted Exploratory Data Analysis (EDA) to extract actionable insights. • Designed a user-friendly Streamlit interface for seamless data input and result visualization.
  • C
    CREDIT RISK MODELING
    Sep 2023 - Oct 2023 (2 months)
    • Developed a classification model using the Random Forest Algorithm to Classify customer risk rate based on historical data, achieved an accuracy rate of approximately 94%. • Conducted comprehensive data processing, including missing value imputation, outlier detection, and feature scaling to prepare the dataset for model training. • Utilized Variance Inflation Factor (VIF) analysis to identify and mitigate multicollinearity issues among predictor variables, ensuring model stability and interpretability.
  • M
    MARKETING CAMPAIGN DASHBOARD
    Jun 2023 - Jul 2023 (2 months)
    • Developed and implemented a Power BI dashboard to analyze and optimize advertisement profitability and strategy, resulting in a 25% increase in ROI and a 20% reduction in ineffective ad spend. • Transformed and processed client's data by using Power Query and DAX to ensure data completeness and validity. • Provided technical insights on how the client can fully utilize their data by introducing different technologies.