Sai Teja

About Sai Teja

At Anthem, my role as a Senior Full Stack Engineer centers on leveraging technology to craft strategic solutions that propel our organization forward. With a focus on innovation and a keen understanding of core competencies, our team collaborates to deliver robust and scalable systems. Though my education specifics remain private, the expertise I bring to Anthem demonstrates a commitment to continuous learning and professional growth, ensuring that we remain at the forefront of industry advancements.

Experience

1. Sr Data Scientist Architect

   CitiusTech

   Jan 2023 — Present · St Louisville, KY, US

   Worked with various R packages, including knitr, dplyr, SparkR, Causal Infer, and Space-Time, and coded R functions to interface with the Caffe Deep Learning Framework.• Used Pandas, NumPy, Seaborn, SciPy, Matplotlib, Sci-kit-learn, and NLTK in Python for developing various Machinelearning algorithms.• Developed and implemented advanced machine learning algorithms using ChatGPT 3.5 to analyze and extract insights from large datasets.• Containerized applications using Docker, enabling consistent development, testing, and deployment environments across different platforms and environments.• Orchestrated containerized applications at scale using Kubernetes, managing deployment, scaling, and operations across clusters for high availability and reliability.• Established clear guidelines and protocols for responsible deployment and use of Generative AI technologies within organizational settings.• Installed and used CaffeDeep Learning Framework.• Worked on different data formats such as JSON, XML and performed machine learning algorithms in Python.• Conducted rigorous evaluation and validation of ChatGPT models to ensure their effectiveness in solving specific business problems and meeting project requirements.• Used pandas, NumPy, Seaborn, matplotlib, Scikit-learn, SciPy, NLTK in Python for developing various machine learning algorithms.• Focus on integration overlap and Informatica newer commitment to MDM with the acquisition of Identity Systems.• Implemented measures for responsible data management and governance to safeguard privacy and prevent misuse of sensitive information in Generative AI applications.• Implemented and optimized evaluation metrics for RAG models, ensuring the assessment of model performance aligns with project objectives.• Implemented end-to-end systems for Data Analytics, Data Automation and integrated with custom visualization tools using R, Mahout, Hadoop,and MongoDB.