• Employed Agile methodologies to adapt to changing project requirements and iteratively deliver solutions. • Conducted hypothesis tests to evaluate variable relationships, aiding data-driven decisions.• Pioneered the application of natural language processing (NLP) and large language models (LLM) to automate customer feedback analysis, improving response times by 35% and enhancing customer satisfaction.• Leveraged TensorFlow to develop advanced predictive models… Show more • Employed Agile methodologies to adapt to changing project requirements and iteratively deliver solutions. • Conducted hypothesis tests to evaluate variable relationships, aiding data-driven decisions.• Pioneered the application of natural language processing (NLP) and large language models (LLM) to automate customer feedback analysis, improving response times by 35% and enhancing customer satisfaction.• Leveraged TensorFlow to develop advanced predictive models, leading to a 15% enhancement in forecast accuracy for key financial metrics. • Implemented Logistic Regression and GBT Classifier in PySpark, achieving 84% accuracy for customer churn prediction. • Designed and developed dynamic Tableau dashboards that provided real-time insights into key performance metrics, reducing senior management's decision-making time by 30%.• Innovated existing machine learning pipelines by integrating autoML frameworks, reducing model training and deployment times by 60% without sacrificing accuracy.• Led the migration of on-premises data infrastructure to a cloud-based architecture on AWS and GCP, resulting in a 40% reduction in operational costs and a 50% improvement in scalability.• Designed and maintained MySQL databases, implementing pipelines with user-defined functions and stored procedures, reducing daily reporting time. Show less

• Conducted thorough testing and validation of data science models and solutions before deployment, following a structured and rigorous approach typical of Waterfall methodologies.• Conducted time series analysis on sales data, leading to a 30% improvement in forecasting accuracy and reduced inventory costs.• Spearheaded designing and implementing advanced predictive models, including XGBoost, CNNs, and LSTM networks, leading to a 20% improvement in predictive accuracy for… Show more • Conducted thorough testing and validation of data science models and solutions before deployment, following a structured and rigorous approach typical of Waterfall methodologies.• Conducted time series analysis on sales data, leading to a 30% improvement in forecasting accuracy and reduced inventory costs.• Spearheaded designing and implementing advanced predictive models, including XGBoost, CNNs, and LSTM networks, leading to a 20% improvement in predictive accuracy for business-critical forecasts.• Utilized Python's data science packages (Pandas, NumPy, Matplotlib, Seaborn, SciPy, Scikit-learn) for advanced data analysis and modeling.• Architected end-to-end data pipelines using Spark and Databricks, enabling seamless data flow across multiple systems and reducing latency by 50%.• Enhanced data integration processes by implementing real-time ETL solutions with Kafka and AWS Lambda, achieving near-instantaneous data updates and improving decision-making speed.• Implemented time series analysis and supervised/unsupervised learning algorithms (LLM) to extract valuable insights from large datasets.• Leveraged advanced DAX functions in Power BI to build dynamic reports that allowed stakeholders to interact with data in real time, enhancing their ability to derive actionable insights.• Implemented backup and recovery strategies for SQL Server databases, reducing data recovery time.• Demonstrated strong analytical, problem-solving, communication, and presentation skills, increasing team productivity and reducing error rates. Show less