Apr 2026 – Present

• Act as a key modelling and data SME within a WFM function of 70+ staff, advising planners, real-time analysts, and leadership on technical feasibility, data interpretation, and process capability.
• Build FTE scenario models for new business initiatives, quantifying workforce impact of moving work between teams, standing up new functions, or absorbing inflow changes at scale.
• Develop what-if and transition models mapping how changes in one area of the business propagate FTE requirements across the wider organisation.
• Led the end-to-end data modelling and allocation framework design for new workforce functions, from initial scoping through to operationalisation and steady state.

Jul 2025 – Apr 2026

• Designed, developed and maintained 50+ Power BI dashboards, Streamlit applications, and Excel reports supporting WFM operations, planning, and performance reporting up to executive level.
• Extracted, cleaned and modelled workforce data from Snowflake, Salesforce, and SQL sources using Python and dbt, ensuring accuracy and timely delivery across WFM reporting cycles.
• Advised reporting analysts across WFM on data interpretation, query design, and what is achievable within ACC infrastructure constraints.

Jul 2024 – Jul 2025

• Built volume forecasting models using Prophet and LightGBM to predict incoming work inflow across departments, providing the demand signal foundation for FTE planning and capacity modelling.
• Designed and built WFM forecasting pipelines and department-level inflow models from the ground up, replacing ad-hoc manual processes with automated, reproducible workflows in dbt, Snowflake, and Python.

Aug 2023 – Jun 2024

• Built Python automation scripts that eliminated manual stakeholder processes and directly reduced the need for unplanned overtime, delivering measurable cost avoidance for the business.