Pavan D Email & Phone Number

Minneapolis, Minnesota, United States

• Developed and deployed predictive models using Azure Machine Learning to analyze customer lifetime value and identify churn patterns, which increased customer retention.• Developed and deployed GenAI models using Azure Machine Learning for generating human-like text, improving customer interaction through personalized chatbots and virtual assistants.• Collaborated with cross-functional teams to build and optimize Marketing Mix Models using Azure Synapse Analytics, significantly… Show more • Developed and deployed predictive models using Azure Machine Learning to analyze customer lifetime value and identify churn patterns, which increased customer retention.• Developed and deployed GenAI models using Azure Machine Learning for generating human-like text, improving customer interaction through personalized chatbots and virtual assistants.• Collaborated with cross-functional teams to build and optimize Marketing Mix Models using Azure Synapse Analytics, significantly improving marketing ROI.• Designed and implemented LLM-based applications such as chatbots and content recommendation systems, enhancing customer engagement.• Conducted A/B testing and performance evaluations for LLM applications, optimizing model performance and efficiency in real-world deployments.• Developed and maintained predictive models for customer segmentation using Azure Databricks, increasing targeted marketing effectiveness.• Led the integration of Azure data science technologies into existing systems, improving data processing speed and reducing cloud costs.• Integrated Generative AI models to automatically generate personalized content and marketing materials, resulting in an improvement in campaign effectiveness.• Collaborated with engineering teams to deploy GenAI models at scale using Azure, ensuring robust monitoring, performance tracking, and version control across multiple production use cases.• Mentored junior data scientists in using Azure tools and best practices, contributing to improvement in team productivity. Show less

Rahway, New Jersey, United States

• Developed and optimized data pipelines to support genomic data analysis, ensuring secure and scalable storage of large datasets, which improved data retrieval efficiency for advanced analytics and research.• Implemented data ingestion processes for handling real-time data from various sources, reducing processing times and enabling timely insights for decision-making.• Utilized traditional data warehousing and ETL tools (such as SQL and Python) for data modeling, ETL processes, and… Show more • Developed and optimized data pipelines to support genomic data analysis, ensuring secure and scalable storage of large datasets, which improved data retrieval efficiency for advanced analytics and research.• Implemented data ingestion processes for handling real-time data from various sources, reducing processing times and enabling timely insights for decision-making.• Utilized traditional data warehousing and ETL tools (such as SQL and Python) for data modeling, ETL processes, and transforming raw data into structured formats suitable for analysis.• Managed the distributed processing of large-scale genomic datasets using tools like Hadoop and Spark, which reduced analysis times and enabled faster insights generation.• Conducted performance tuning of SQL queries, optimizing execution times for faster access to critical data in research and analytics projects.• Automated data processing workflows using scripting and scheduling tools like Cron, improving operational efficiency and reducing manual interventions.• Developed custom Python scripts for data wrangling, feature extraction, and preprocessing, supporting machine learning model development in clinical research.• Collaborated with cross-functional teams to migrate legacy systems to newer, more efficient data platforms, ensuring seamless data access and integration, and improving productivity.• Designed and implemented data validation and quality assurance processes, ensuring the accuracy and reliability of datasets used in advanced research and machine learning models.• Managed the efficient archiving and retrieval of large datasets, optimizing storage costs while maintaining accessibility for research and development purposes.• Led the integration of data analysis tools with third-party platforms, enhancing collaboration between data science and engineering teams. Show less