I am a Toronto-based strategic FP&A and financial modeling consultant with a financial economics background. My work sits at the intersection of practical business finance and rigorous quantitative reasoning.
I am a strategic FP&A and financial modeling consultant based in Toronto, Canada. I work with businesses across industries that face complex financial, strategic, or operational decisions, where the question is not just what the numbers say, but what they mean and what to do about them.
My path into finance runs through two distinct sources: graduate-level training in financial economics, econometrics, and mathematical modeling on one side, and hands-on corporate FP&A experience in a real business environment on the other. That dual foundation shapes how I approach financial problems, with both analytical rigor and practical business judgment.
My FP&A experience spans budgeting, forecasting, variance analysis, management reporting, margin analysis, and cash-flow planning, in a business environment with genuinely complex drivers: pricing dynamics, product and customer mix, gross margin pressure, capacity constraints, backlog, and working capital.
That experience taught me how financial planning works under real conditions: imperfect data, competing priorities, and leadership that needs clarity under time pressure. I have built financial models and planning processes under those conditions, designed to be understandable, defensible, and directly useful for decision-making.
My graduate training in economics and econometrics gives me analytical tools that rarely appear in standard FP&A work: estimating relationships between business variables, separating the effects of price, volume, and mix, evaluating whether a change in the numbers is meaningful or just noise, and quantifying uncertainty in a way that is useful for decisions, not just acknowledged.
This includes revenue-driver analysis, demand and sales forecasting, price sensitivity and elasticity thinking, regression-based modeling, and scenario analysis that reflects genuine uncertainty rather than arbitrary point estimates.
Alongside my statistical background, I have deep experience in mathematical programming and optimization, finding the best allocation of resources, pricing strategy, or operational decision given a set of real-world objectives and constraints. This background shapes how I approach business decisions: not as isolated questions to be answered separately, but as integrated problems with tradeoffs that need to be modeled explicitly.
I use AI tools, including Claude, as part of a modern analytical workflow, structuring complex problems, drafting management narratives, improving model documentation, and building reusable frameworks more efficiently. AI does not replace financial judgment, business understanding, or modeling expertise. It amplifies them when applied carefully.
My goal is to help businesses thrive through creative, rigorous analysis and well-grounded strategy, building the kind of decision-support work that turns complex financial questions into clear, actionable direction. The tools, templates, and frameworks on this site are part of that effort: making serious analytical thinking accessible and practical for real business decisions.