John Park

Founded and built an agentic AI systems consultancy delivering multi-agent AI infrastructure and automation for finance broking, real estate, accounting, coaching, home services, and property management businesses. Architected and deployed voice agents, RAG systems, LLM infrastructure, and CRM/workflow automations, including compliance-focused agents and lead-to-CRM pipelines.

Led customer churn analysis using Python and SQL to identify at-risk segments and support retention improvements. Built Tableau dashboards for real-time wagering KPIs and optimized SQL queries to model customer lifetime value for promotional offer decisions.

Built automated financial risk reporting pipelines using Python and AWS SageMaker to reduce manual reporting time and errors. Created Power BI dashboards tracking loan performance and default rates for C-suite visibility during a restructuring period.

Performed data cleansing and standardization for enterprise audit preparation, supporting data accuracy for a warehouse migration. Contributed to preparation work for audit readiness in an enterprise setting.

Worked on a master’s capstone data science project applying predictive modeling to environmental datasets. Built Python and R models and presented results via Tableau dashboards to non-technical stakeholders.

Completed a Master of Data Science at the University of Melbourne (2020–2022), including a capstone project on rumour detection on Twitter using machine learning and sentiment analysis (85%+ accuracy).

Completed a Bachelor of Commerce (Finance) at the University of Auckland (2015–2019).

Grade: Certificate of Distinction (2019)

Completed a Bachelor of Science (Statistics) at the University of Auckland (2015–2019). Earned a Certificate of Distinction in Statistics (2019) and received the Statistics NZ Internship Scholarship.