Patrick Reza Schnurbusch
Richmond Hill,ON
Summary
Analytics professional with expertise in forecasting, statistical modeling, and analytical infrastructure supporting executive decision-making and long-range planning. Experienced in building automated reporting systems, demographic and geographic analysis frameworks, and predictive models using R, Python, and SQL. Strong background translating complex datasets into scalable decision-support tools for stakeholders across operational, financial, and strategic environments.
Overview
7
7
years of professional experience
Work History
Principal Consultant
17567863 Canada Inc.
01.2026 - Current
- Develop predictive and analytical frameworks supporting demographic analysis, regional planning, and location-based strategy using Census Population Profile data at the DAUID level.
- Build reusable analytical products and automated reporting systems that generate customized outputs across geographic regions and stakeholder groups.
- Design Shiny applications supporting workflow automation, request routing, and operational decision-making.
- Create segmentation models using behavioural, demographic, and geographic variables to identify distinct population groups and improve targeting precision.
- Build multi-source analytical workflows integrating census, demographic, and geographic datasets to support long-range planning and scenario analysis.
- Conduct time-series analysis of engagement patterns to identify behavioural cycles, optimize communication timing, and improve outreach performance.
- Deliver strategic analytical studies integrating multiple data sources to support planning under uncertainty and resource allocation decisions.
- Develop scalable reporting infrastructure, reducing manual analytical effort while improving reproducibility and stakeholder access to insights.
Data Analyst - Forecasting, Machine Learning & Geospatial Analytics
Conservative Party of Canada
04.2019 - 12.2025
- Developed statistical forecasting models using ARIMA, SARIMA, regression, and machine learning techniques to predict month-ahead revenue using millions of transaction records.
- Built probabilistic models analyzing donation behaviour and trend shifts across fundraising channels to support strategic planning and performance forecasting.
- Designed end-to-end automated analytics pipelines in Python and R, generating recurring forecasts and executive financial reports.
- Reduced reporting timelines from multiple days to hours through workflow automation and parameterized reporting systems.
- Built predictive frameworks supporting targeted fundraising strategies associated with sustained 6-figure cumulative revenue across multiple campaign cycles.
- Conducted demographic, spatial, and geographic analysis using R (sf, spdep, leaflet) and QGIS to identify regional trends and optimize targeting strategy.
- Performed NLP analysis using topic modelling, clustering, and n-gram analysis to extract insights from donor communications and messaging performance.
- Built scalable geospatial reporting infrastructure delivering analytical outputs to over 1,000 geographically distributed stakeholders, leveraging electoral data to infer competitive intelligence from multiple data sources.
- Developed executive-facing dashboards and reporting tools communicating financial, operational, and strategic insights.
- Collaborated cross-functionally with fundraising, leadership, digital operations, campaign teams, and IT stakeholders to translate analytical outputs into actionable decision support.
- Acted as a central analytics partner during high-volume operational periods, translating business questions into structured analytical frameworks and measurable outcomes.
Education
Data Analytics - Big Data & Predictive Analytics
Ryerson University
01.2017
Bachelor of Arts (Honours) - Political Science
University of Toronto
06.2015
Skills
- Time-Series Forecasting (ARIMA, SARIMA)
- Statistical Modeling
- Predictive Analytics
- Scenario & Simulation Modelling
- Revenue & Trend Analysis
- Sensitivity Analysis
- R
- Python
- SQL
- Hadoop / Hive / Spark
- Workflow Automation
- Automated Reporting Pipelines
- Executive Dashboards
- Parameterized Reporting
- Tableau
- Shiny
- GIS
- QGIS
- Spatial Statistics
- Census & Demographic Data
- Regional Trend Analysis
- XGBoost
- Regression
- NLP
- Segmentation Modeling
- Classification & Clustering
Selected Analytical Projects
- Multivariate Revenue Forecasting, Developed multivariate forecasting models using weekly retail revenue data across 50 locations., Integrated economic and environmental indicators including CPI, fuel prices, employment, and weather variables., Evaluated temporal patterns and regional variation using advanced forecasting workflows in R.
- Geospatial & Demographic Analysis, Integrated census, electoral, and geographic datasets to identify population-level trends and regional variation., Built geographic analytical frameworks supporting regional planning and targeting decisions.
- Automated Analytics Infrastructure, Designed automated reporting pipelines generating recurring executive-ready outputs and performance summaries., Reduced manual reporting requirements while improving consistency and reproducibility.
- Segmentation Modelling for Behavioural and Value-Based Analysis, Developed behavioural segmentation models using RFM frameworks to identify high-value engagement cohorts., Applied segmentation analysis to improve targeting precision and support resource allocation decisions.
Timeline
Principal Consultant
17567863 Canada Inc.
01.2026 - Current
Data Analyst - Forecasting, Machine Learning & Geospatial Analytics
Conservative Party of Canada
04.2019 - 12.2025
Data Analytics - Big Data & Predictive Analytics
Ryerson University
Bachelor of Arts (Honours) - Political Science
University of Toronto