Business Systems & Operations Specialist | Automation , AI & Digital Transformation

Lead an organizational transformation and technology company that helps organizations redesign operations through strategy, systems, technology, data, and AI.

Diagnose organizational and operational problems, translate requirements into workflows and digital infrastructure, and deliver systems involving automation, data platforms, APIs, and internal tools. Build reusable capabilities across healthcare, development programmes, fintech, and business environments using the Diagnose, Design, Build, Deploy, Improve approach.

Supported complex programme operations involving workforce and fellow records, facilities, deployment workflows, business rules, and digital infrastructure.

Translated allocation requirements into operational logic including LGA capacity rules and preference-based matching. Contributed to registry, portal, authentication, reporting, and administrative systems using Next.js, React, TypeScript, Supabase/PostgreSQL, Vercel, APIs, and database security controls.

Helped transform a source dataset of 1,729 records, importing approximately 1,487 usable records while identifying exclusions and genuine data errors. Supported seeding operations across 37 states, approximately 1,393 facilities, and approximately 1,488 nurse registry records.

Co-founded the organization and led business operations, ensuring that operating processes were documented, structured, and executed consistently.

Worked on process documentation, workflow discipline, accountability, operational controls, and execution visibility. Developed practical understanding of how incentives, controls, and operational systems influence organizational performance.

Performed structured data and video annotation work according to project guidelines, evaluation criteria, and quality standards.

Worked in distributed remote workflows requiring consistency, attention to detail, and adherence to defined labeling requirements.

Worked in an AI and data environment involving structured annotation, evaluation, and data-quality workflows.

Developed practical exposure to AI data production processes and quality requirements.

Worked in a structured remote and distributed AI/data environment with defined task and quality requirements.

Built experience completing data-related work consistently within project guidelines and evaluation standards.

Bachelor's degree in Electrical and Electronics Engineering.