Toronto, ON • LinkedIn | GitHub
Software engineer with Engineering Physics background and hands-on experience building production tools and data systems. Develop reliable Python applications, ETL pipelines, and automated testing workflows from problem definition to deployment. Experience with API integration, database design, and performance optimization.
Programming: Python, SQL (Postgres/MySQL/SQLite), learning Go; MATLAB, R; Bash, Powershell
Data: Pandas, NumPy, scikit-learn; HDF5/CSV/JSON pipelines; ETL and data models; audit-friendly documentation
App & UI: PySide6, PyQtGraph; packaging with PyInstaller; logging and config management
Testing & Quality: pytest, CI/CD foundations; schema checks, range checks, duplicate detection; reproducible pipelines
Visualization & reporting: Matplotlib, Tableau; KPI definition and clear readouts
Cloud & APIs: GCP, AWS EC2; REST API integration
Hardware & Instrumentation: SCPI control with precision; calibration workflows; Raspberry Pi prototyping
Collaboration: Stakeholder-facing demos, concise writeups, decision-focused presentations
Junior Software Developer — FUS Instruments, Toronto, ON — Oct 2024 - Present
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Replaced fixed wait timers with device acknowledgements in scope control, eliminating flaky runs and improving measurement reliability. Eliminated hardware race conditions, improving reliability by 20% and routine speed by 50%
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Refactored a large single-file tool into modules for instrument I/O, processing, and UI, enabling targeted unit tests and easier changes.
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Improved plotting responsiveness by sampling only the data visible at the current zoom and window size; kept the UI responsive with large files.
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Built an interactive time-windowing feature that lets users select a range on the plot, recompute frequency views, and save a new file with clear naming.
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Designed Pandas and HDF5 pipelines that reduced processing time by over 30% and improved reproducibility with versioned transforms.
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Packaged and shipped Windows executables with PyInstaller, adding logging and environment configuration to simplify lab deployments.
Engineering Technician — FUS Instruments, Toronto, ON — April 2024 - Oct 2024
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Streamlined hardware to software communication for precision instruments, improving measurement consistency and throughput.
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Developed diagnostic workflows that reduced device downtime and tightened feedback loops between engineering and operations.
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Collaborated with researchers to verify signal integrity and document procedures supporting consistent analyses
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Established documentation process with templates to ensure consistent and clear documentation for all process, software, and tools
Team Lead, Client Success — Exactus Energy, Toronto, ON — 2017 - Oct 2023
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Built and led a 6-person team; set up KPI and SLA definitions, cadences, and ownership across the workflow.
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Created executive-ready SQL Tableau dashboards with monthly readouts that aligned teams to targets and clear actions
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Delivered measurable outcomes: retention up 15%, service efficiency up 25%, turnaround times down 15% through process and data optimizations
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Translated operations signals into metrics, alerts, and corrective actions in partnership with operations and engineering
Sr. Client Success Manager — Exactus Energy, Toronto, ON — 2017 - Oct 2023
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Automated KPI pipeline for over 5,000 projects annually; enabled consistent monthly reporting and ad hoc executive summaries
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Added data quality checks and documentation that improved trust in metrics and reduced reconciliation time.
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Identified bottlenecks across intake to completion and implemented fixes reflected in dashboard trends.
Client Success Manager — Exactus Energy, Toronto, ON — 2017 - Oct 2023
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Managed a high-volume portfolio while establishing baseline KPIs, SLA expectations and reporting routines
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Coordinated projects with clients and internal teams by clarifying requirements, setting clear milestones, and ensuring timely delivery of solutions that reduced rework and improved client satisfaction.
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Captured recurring issues, formalized playbooks, and laid the groundwork for later automation and scale.
Solar Technician — Exactus Energy, Toronto, ON — 2017 - Oct 2023
- Performed site surveys and structural inspections in customers' homes, produced AutoCAD PV layouts and permit-ready packages, and coordinated with installers, balancing technical accuracy with clear communication to ensure safe, code-compliant installations.
SplitterApp - Python expense manager
Developed a Python/PySide6 desktop tool for managing shared expenses. Features include adding and removing transactions with unique identifiers, automatic cost splitting and real-time balance updates, and seamless Google Drive synchronisation. It provides an intuitive dark-themed interface, uses CSV-based offline storage for resilience, and is packaged for easy installation. The codebase is covered by comprehensive pytest-driven tests to ensure reliability.
E-commerce Analytics Database Project - SQL Data Engineering
Designed and implemented an ETL pipeline to clean, transform, and analyze e-commerce web traffic data using SQL. Developed data quality validation processes, resolved inconsistencies across multiple data sources, and optimized database schema for scalable analytics queries. Applied systematic data cleaning techniques and identified opportunities to establish primary keys and normalize database structure into a proper relational database architecture.
Statistical Modeling & API Integration Project - Python
Built a data pipeline integrating multiple APIs (Yelp, Foursquare, Toronto Bike Share) to analyze relationships between point-of-interest data and bike availability. Developed Python scripts to extract, clean, and merge heterogeneous datasets, performed exploratory data analysis with visualization, and implemented multivariate linear regression modeling. Created SQLite database for processed data and conducted statistical analysis to identify geographic patterns in urban mobility data.
Wholesale Dataset Unsupervised Learning
Led a short end‑to‑end unsupervised‑learning project on a grocery wholesaler dataset: cleaned and visualized the data, then used K‑Means, hierarchical clustering, and PCA to uncover customer segments and derive actionable retail insights. This helped identify distinct purchasing patterns to inform marketing and inventory decisions.
Exoplanet Classification with XGBoost
Designed a full machine-learning pipeline on NASA's Kepler dataset. Cleaned and encoded data; explored several models to determine best performance (XGBoost). Applied feature engineering and resampling, cross‑validated the model and achieved ~0.91 weighted accuracy and ~0.88 macro F1‑score, illustrating robust classification of exoplanet candidates.
Data Science Diploma, Lighthouse Labs - Toronto, ON, Canada
B.A.Sc. Engineering Physics, Mechanical Option, Queen's University - Kingston, ON, Canada