Lead Ml Scientist, Cloud, Devops
Led the DataMesh initiative, designing and implementing a scalable and cost-effective solution for serving the DataLakes built. Successfully scaled the architecture to support nearly 50 different data products from various online sources, meeting the growing data serving needs of the company.Actively participated in product and business analysis for pitches and investor calls, providing valuable insights and contributing to strategic decision-making.Managed Cloud DevOps for Taiyo's ML pipelines, ensuring efficient and scalable CI/CD pipelines. Resulted in faster release cycles and increased productivity. Also responsible for GCP administration, including IAM, price management, network management, and microservices infrastructure.Developed and maintained Taiyo ML Pipelines, a scalable package that supported analysts and data scientists in building and managing ML models and data analytics needs. this streamlines MLops we had to perform and made it possible to build 500 ML signals on a daily basis.Collaborated with UI/UX, frontend, and backend teams to deliver products such as Country Risk Scanner, Investments AI, Stock Market Scanner, ML Pipelines and Taiyo Dashboard Store. Ensured seamless integration and smooth functioning of all components.Implemented best practices for data engineering, Python, SQL, and GCP, ensuring code performance, quality, integrity, and security.Actively contributed to Taiyo ML Pipelines as a maintainer, overseeing issues, feature requests, and managing releases for other ML workflows used in their products.Worked on building products and solutions for Investments AI, Projects and Tenders Insights, Taiyo ML Pipelines and maintain existing tech stack.