Anudeep Ayinaparthi Email and Phone Number

DATA SCIENTIST – LEGAL & GENERAL INVESTMENT MANAGEMENT VIA KUBRICK GROUP, LONDONMay 2023 – Present• Created an automated workflow using Alteryx to convert a large Fund Data Excel spreadsheet into smaller, customized tables.• Proactively engaged with stakeholders to gather feedback and demonstrated strong interpersonal skills and adaptability in responding to changing demands, ensuring seamless integration of data processes, and meeting evolving business requirements.• Saved significant time for business analysts by eliminating manual table creation, resulting in a more efficient and streamlined process.• Created an insightful dashboard highlighting discrepancies between production and test data, providing stakeholders with actionable insights.• Developed Python scripts for data cleaning and automated data uploading to S3, utilizing date partitions for efficient data indexing.• Empowered stakeholders to make informed decisions by presenting key information through the dashboard.• Ensured data accuracy and real-time updates by automating the daily data uploading process, resulting in a consistently refreshed dashboard.DATA SCIENTIST – AXA VIA KUBRICK GROUP, LONDONDecember 2021 – March 2023• Utilized SQL skills to extract and analyze data from a large dataset, leading to quantification of opportunities and data-driven recommendations for stakeholders.• Created a machine learning model to identify customer propensity for shop around behaviour during renewal window.• Utilized Python libraries (Pandas, Numpy, Scikit-learn) for data transformation and preparation for model training, including imputation, normalization, and feature engineering.• Applied exploratory data analysis (EDA) techniques to identify patterns, correlations, and anomalies in the data and used VIF analysis to remove correlated features.• Trained and fine-tuned an XGBoost model with hyperparameter tuning using GridSearch to optimize performance, evaluated using k-fold cross-validation.• Utilized performance metrics (accuracy, precision, recall) to assess and communicate model performance effectively.• Developed and implemented a PySpark-based solution for a large-scale analytics project to identify the best discount to offer customers at renewal, resulting in improved customer retention strategies.• Conducted complex data transformations, including joins and feature engineering, to create a high-quality dataset for the discount optimization project.