Practical, results-driven Software & ML, and Reservoir Engineer with 7+ years’ commercial experience building backend systems and delivering applied data science and machine learning solutions in regulated and product-led organisations. Strong background in fullstack-based development, AI Research/Security and ML stack (Azure ML, Kaggle). Skilled in designing data pipelines, ETL workflows and cloud-hosted ML models. Track record of refactoring legacy systems, improving model accuracy, and delivering measurable business outcomes (reduced verification times, improved prediction reliability, significant cost and risk reductions). Comfortable in Agile teams, collaborating with technical and non-technical teams. Track record of delivering oil-industry reservoir engineering projects and winning leadership awards.
I led a small team of 3 to build and deploy a streaming dataset plugin for the Ocean Protocol. I was technically in charge of development, code review, and bug fixes. The other team members were a data scientist and a product manager. We were able to deliver on target deliverables after winning the Ocean DAO grants two times.
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I exemplified strong technical, leadership, and entrepreneurial ability, working with a small team made up of myself, a DevOps engineer, and a non-technical Co-founder to build an MVP that won us an award from Microsoft Startup Founders Hub.
I also architected the entire solution using a hybrid approach (Microservice and Monolith), with the Microservices implemented on a Just-In-Time basis to manage complexities, enable scaling, and timely go-to-market implementation. A recommendable approach for a startup, this helped us to gain meaningful traction.
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