Yoshith Kotla Email & Phone Number

New York, Ny, Us

Somerset, New Jersey, United States

Directed and approved AI implementations and strategies, ensuring alignment with business objectives and compliance with industry regulations. Acted as the key decision-maker for AI initiatives, collaborating with stakeholders to deliver impactful, data-driven solutions. Led the implementation of Generative AI solutions for clinical document generation, fine-tuning open-source models like LLAMA 3.1, Mistral, and GPT-4 for customized and formatted reporting. Built synthetic healthcare data pipelines to ensure HIPAA compliance, designing custom evaluation metrics for medical terminology accuracy and optimizing model performance through inference parameter tuning. Streamlined LLMOps workflows for efficient model deployment, monitoring, and scalability, reducing infrastructure costs by 30%. Designed Retrieval-Augmented Generation (RAG) pipelines, implementing advanced query translation, routing, and indexing techniques, achieving a 45% improvement in Mean Reciprocal Rank (MRR) and a 30% reduction in hallucination rates. Developed inference engines using NLP tools such as LangChain to transform unstructured technical documents into structured insights. Automated data processing workflows to improve compliance efficiency and support real-time decision-making in highly regulated environments. Applied data cleansing and preprocessing techniques to ensure high-quality datasets for machine learning model training and evaluation. Utilized big data frameworks such as Apache Spark and Hadoop to process and analyze large-scale datasets in cloud environments. Partnered with cross-functional teams to define business challenges and translate them into actionable machine learning tasks, ensuring alignment with strategic objectives.

Irving, Texas, United States

Architected, designed, and led the development of an AI-powered big data product for detecting data quality issues and irregularities using supervised and unsupervised machine learning algorithms in Apache Spark, securing $1M in startup funding. Managed the full software development lifecycle in an Agile/Scrum environment, including defining coding standards, conducting code reviews, managing source control, and overseeing testing and deployment processes. Designed and implemented a hybrid recommendation system in AWS, integrating collaborative and content-based filtering techniques to match medical practitioners with patients, utilizing AWS S3 for batch data processing and Amazon Kinesis for real-time streaming. Deployed and tracked machine learning models using Amazon SageMaker, ensuring real-time personalized recommendations and scalability for processing high-volume datasets. Developed enterprise-level knowledge graph solutions using Neo4j and Stardog, optimizing graph ontologies and data models to enhance semantic search, advanced querying, and data integration processes. Implemented Microsoft Azure-based big data solutions for retail pharmaceutical data, developing Spark-based ETL pipelines and creating star and snowflake schema models to optimize data warehousing performance.

Hyderabad, Telangana, India

Applied Agile methodology to manage and execute various phases of the Software Development Life Cycle (SDLC), ensuring iterative development and continuous delivery. Designed and developed data pipelines using Python to preprocess medical images and streamline the training and testing of machine learning models. Led the end-to-end setup and deployment of a Hadoop platform from scratch, serving as the primary resource for infrastructure development. Optimized Hive and Pig scripts by resolving performance bottlenecks, refining joins, group operations, and aggregation logic, and enhancing the efficiency of MapReduce jobs. Improved the performance of SSIS packages by implementing parallel execution, removing unnecessary sorting, and leveraging optimized SQL queries and stored procedures. Evaluated and proposed cost-effective architectures in Azure, recommending strategies to optimize data infrastructure and ensure resource efficiency. Designed, developed, deployed, and maintained large-scale Tableau dashboards to provide actionable insights for Product Insights, Device Networking, and Cox Premise Equipment, driving data-driven decision-making.

Hyderabad, Telangana, India

Developed middleware applications using Java Servlets, JavaBeans, Microservices, and Spring framework, focusing on feature enhancements and issue resolution for improved system functionality. Implemented robust database connectivity using JDBC with MySQL as the backend, enabling seamless data integration and optimized data management. Designed and optimized intelligent routines to extract and process terabytes of data across multiple hospital sites, significantly improving data extraction efficiency. Conducted GAP analysis to compare "As-Is" and "To-Be" processes, performed risk assessments of existing systems, and evaluated the benefits of new system implementations to align with organizational goals. Created dynamic reporting solutions using Excel and Power BI, sourcing data through SQL queries to deliver actionable insights and support data-driven decision-making

Jodhpur, Rajasthan, India

Designed and implemented advanced statistical analysis and machine learning models, including clustering, association rules, linear and logistic regression, decision trees, Naive Bayes, text mining, optimization, bagging, boosting, random forests, and neural networks. Developed AWS Glue jobs using Spark and Python to perform data transformations on unstructured datasets, loading processed data into DynamoDB for optimized querying. Processed, cleaned, and modeled business data using SQL and Python libraries such as NumPy, Pandas, Matplotlib, and ggplot2 to deliver actionable insights and visualizations. Streamlined deployment processes by implementing CI/CD pipelines for automated testing, integration, and deployment of data solutions, improving development efficiency. Deployed and managed scalable data solutions on Azure platforms, including Azure Data Factory, Azure Cosmos DB, and Azure Synapse Analytics, to ensure high availability and performance.

Master Of Science - Ms, Data Science

Bachelor Of Technology - Btech, Computer Science