Chaitanya KAKARLA

Achieved successful implementation of an end-to-end pipeline for loading content from Google Drive into S3 storage.

Delivered parsed content that enabled the creation of informative knowledge graphs on disease-related topics.

Enhanced querying capabilities of knowledge graphs against synthetic patient data, improving data accessibility.

Optimised API and pipeline performance through the use of FastAPI, showcasing technical proficiency.

Created comprehensive knowledge graphs using Python ontologies and SPARQL, driving data insights.

• Streamlined patient data retrieval via GraphQL queries, increasing efficiency of knowledge graph interactions.
• Developed an intuitive Streamlit UI for editors, facilitating content loading and quality assurance processes.

• Led the design of a scalable and secure health data platform aligned with project objectives.
  Facilitated integration by analysing diverse data sources and validating ingestion processes.
  Recommended tools to enhance data quality standards in line with industry best practices.
  Ensured platform compliance with security standards and regulations such as HIPAA and GDPR.
  Engaged stakeholders to capture requirements and identify gaps for a robust platform solution.
  Conducted technology comparisons to identify optimal tools and tech stack for the platform.
  Produced detailed technical documentation to support project final deliverables and findings.

• Assisted in enhancing user experience by automating repetitive tasks with Python scripts.
• Supported implementation of real-time monitoring tools for swift anomaly detection in data streams.
• Contributed to the design of robust databases for secure storage and quick retrieval of vital business data.
• Aided in creating interactive dashboards using BI tools like Tableau to empower non-technical stakeholders with actionable insights.

• Assisted in building pipeline using Python's Flask to ensure smooth operation of AI modules.
• Developed AI modules leveraging pre-trained computer vision models for analysing video assets from diverse S3 accounts producing user-friendly JSON results.
• Enhanced user interface to effectively display AI findings improving user experience.
• Helped integrate GitHub for version control to facilitate collaborative code management.
• Supported implementation of CI/CD workflows to automate testing and deployment processes ensuring operational efficiency.
• Conducted code reviews to maintain quality and identify areas for improvement.
• Followed agile methodologies for flexibility and client-focused project management.
• Adhered to structured software development lifecycle including planning, development, testing, and deployment.

• Achieved enhanced data processing through development of scalable data pipeline via AWS Glue.
  Delivered secure and efficient data storage solutions employing Amazon S3 and Redshift.
  Optimised data management within AWS ecosystem, ensuring seamless integration and operational flow.
  Forecasted student demand effectively by developing machine learning model with Python.
  Enabled actionable insights for stakeholders through impactful data visualisation with Power BI.
  Improved data pipeline functionality through efficient scripting and development in Python.
  Ensured data accuracy and performance through effective database management with Oracle SQL and MySQL.
  Streamlined collaboration and code management by utilising GitHub for version control.

• Assisted in development of customer segmentation model by employing machine learning techniques to classify customers based on behavior and transaction data.
• Supported data preprocessing and feature engineering efforts, utilizing Python and SQL to cleanse and transform raw data for improved model outcomes.
• Contributed to training and optimization of machine learning models by selecting suitable algorithms and hyperparameters to enhance performance for segmentation tasks.
• Facilitated data analysis and visualization activities, presenting insights to stakeholders through data visualization tools and generating reports on identified trends.
• Collaborated with data science team to deploy customer segmentation model into production, ensuring integration and real-time data processing.