I Build AI Systems That Automate the Work.

In February 2025, after almost two years as a Data Analyst at Banco Galicia, I left to do something I'd wanted for a long time: live abroad and get real immersion in another language and culture.

I started with volunteer work — Howzit Hostel in Hawaii and Casa Wolaba in Costa Rica — learning to navigate unfamiliar environments with no structure and no support network. Then I moved to Australia on a Working Holiday visa (subclass 462), working as a bartender, waiter, receptionist, and events crew across Blue Mountains, Gold Coast, and Cairns.

Not a gap — a deliberate choice.

As a data analyst within the Change Management and Continuous Improvement team, I had full ownership of the customer service data domain — covering both digital and phone channels, impacting over 700 agents.

Phase 1 — Operational analytics. I maintained and enhanced Power BI dashboards, developed new reporting solutions, and optimized SQL queries for performance and reliability. I owned service forecasting — including staffing models for holidays and special events — critical in a 24/7 operation. Using queue theory, I built a decision-support dashboard that connected demand and supply metrics, providing utilization thresholds to manage peak periods without increasing headcount.

Phase 2 — Data model for platform migration. In the later stage of my role, the bank migrated its customer service platform to a new system. I was responsible for the end-to-end design of the new data model: I analyzed 50+ source tables in Snowflake, defined the logic for fact and dimensional tables based on the area's future reporting needs, and wrote the SQL scripts to build them. The output was 3 fact tables in Teradata — consumable, reliable, and ready for analytics and dashboards. A specialized data engineering team handled infrastructure and automation; I owned the business logic, table design, and development.

As a customer service officer in the digital channel, I developed a strong understanding of banking operations, customer pain points and service workflows.

I identified a key operational gap: customer satisfaction KPIs were only available after day-end, limiting the ability to adjust performance during the day.

Using daily survey data, I built an Excel-based tracking tool that allowed teams and leaders to monitor performance in near real time. Although developed outside my formal responsibilities, the tool was quickly adopted by leadership and scaled across multiple teams, impacting over 350 agents.

This initiative increased my visibility within the sector and contributed to my transition into a data-focused role.

During my internship in sales administration and commercial planning, I gradually gained the trust of my supervisors through consistent performance and reliability.

This allowed me to take responsibility for tasks such as preparing monthly performance reports and supporting commercial planning activities.

The role provided my first exposure to structured reporting, performance analysis and cross-functional collaboration within a commercial environment.