Experience

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  SWAGG TECHNOLOGIES

  • Bangalore, India

  • Junior Data Scientist

    • Mar 2022 - Oct 2023
    • Bangalore, India

    • Collected and analyzed customer data to identify patterns and key indicators of potential churn.• Applied statistical methods to extract actionable insights from customer data for churn prediction.• Developed a churn prediction model using machine learning algorithms and statistical techniques.• Collaborated with cross-functional teams to improve model accuracy.• Implemented customer retention strategies, resulting in a 5% reduction in churn rate.• Applied machine learning algorithms and statistical techniques for accurate churn prediction.• Enhanced collaboration with cross-functional teams to align strategies and goals for effective churn reduction.

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  Rubixe

  • India

  • Data Science Intern

    • Jun 2021 - Mar 2022
    • India

    Project: Portuguese Bank Marketing• Utilized SQL Alchemy to extract relevant data from SQL database and executed complex SQL queries to gather data for analysis.• Employed statistical methods and visualization tools to gain insights into the dataset.• Identified key patterns and trends to inform subsequent modeling decisions, and applied data cleaning techniques.• Implemented machine learning algorithms to predict client subscription to term deposit.• Utilized logistic regression and decision trees, as well as iteratively tuned hyperparameters to enhance predictive accuracy.• Assessed model performance using precision, recall, F1 score, log loss, and AUC-ROC curve, and improved model performance.Project: Credit Card Approval• Significantly reduced processing time for credit card approvals from weeks to hours.• Implemented bagging and boosting supervised machine learning algorithms for faster decisions.• Extracted structured data from the SQL database using SQL Alchemy.• Conducted exploratory data analysis to identify critical features, and preprocessed data to ensure suitability for modeling.• Engineered features to enhance the algorithm's ability to discern creditworthiness.• Applied bagging and boosting techniques to improve the accuracy of credit card approval predictions.• Employed ensemble learning methods for enhanced model robustness, and conducted hyperparameter tuning to optimize the model's predictive capabilities.

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  Eximius Design

  • Bengaluru, Karnataka, India

  • Software Engineer

    • Feb 2018 - Apr 2019
    • Bengaluru, Karnataka, India

    • Conducted in-depth analysis on historical transaction data to identify patterns indicative of potential fraud.• Utilized statistical methods and machine learning techniques to extract actionable insights.• Implemented efficient data preprocessing steps to clean, transform, and feature engineer the data for fraud detection.• Ensured data quality and prepared the dataset for effective model implementation.• Developed and implemented a fraud detection model using machine learning algorithms.• Applied advanced techniques to enhance the accuracy of the model and achieve a 10% reduction in fraud incidents.• Engaged in regular communication with stakeholders to gather feedback and incorporate improvements.Client: Zebra TechnologiesProject: Trailer Monitoring Unit• Updated firmware of the Trailer Monitoring Unit device to enhance its functionality and performance.• Conducted Regression testing, Retesting, Functional testing, and BAT testing to ensure software reliability.• Contributed to achieving the project goal of providing a load efficiency solution, and integrated software updates seamlessly.• Minimized maintenance costs, reduced damage loss, and improved overall operational efficiency.• Worked closely with stakeholders to address project requirements and ensure successful implementation.• Implemented testing methodologies to validate the reliability and effectiveness of the updated firmware.

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  Wesnia Info Solutions Pvt Ltd

  • Bengaluru, Karnataka, India

  • Software Engineer

    • Jun 2015 - Feb 2018
    • Bengaluru, Karnataka, India

    Project: SAS RAID Controller Card• Verified and validated features of SAS RAID Controller cards, focusing on ORCM and ORLM, ensuring adherence to specifications.• Orchestrated the writing and execution of comprehensive test cases, and assessed RAID levels (R1, R5, R6, R10, R50, R60).• Spearheaded the firmware updating process of device, oversaw regression testing and functional testing to enhance performance.