Victoria Farkas victoriafarkas9@gmail.com • linkedin.com/in/victoria-farkas-617262262
English (native) • French (B1 Certified) • Hungarian (heritage speaker) PROFILE Master of Data Science student at UBC with a strong foundation in rigorous statistical modelling and full-stack software development. Experienced in engineering secure data pipelines, managing population-scale datasets (10,000+ variables), and building interactive frontend data applications. Brings a track record of leading data intake projects across major government and health institutions, with deep familiarity with privacy-preserving methodology and data governance frameworks. Multilingual communicator adaptable to international and fast-paced environments. TECHNICAL SKILLS Programming & Analysis: Python (Pandas, PyTorch, scikit-learn, NumPy, OpenCV), R, SQL, C, SPSS Tools & Platforms: Tableau, Git, Plotly, Shiny, Streamlit, Docker Domains: Health data governance, privacy-preserving data linkage, machine learning, statistical modelling, UI/UX design EDUCATION Master of Data Science (MSc.) — University of British Columbia 2025 – Present • Recipient of the $10,000 Domestic Student Excellence Scholarship, awarded for outstanding achievement in data science Bachelor of Science, Behavioural Neuroscience — University of British Columbia 2019 – 2024 • Coursework spanned research statistics, experimental design, human subjects ethics, and cognitive systems Cours de Civilisation Française — La Sorbonne, Paris Jan – Jun 2019 • Full academic immersion; certified in conversational French (A2/B1) WORK EXPERIENCE Data Scientist — UBC Data Science Club Dec 2025 – Present • Embedded as data scientist on a Computer Vision research project led by a Master of Physiotherapy candidate at UBC • Developed a classification pipeline to identify exercise types and evaluate form quality from raw video data • Optimized feature selection by identifying key joint angles and spatial relationships, significantly reducing the dimensionality of the input data without sacrificing predictive power

Data Access / Management Assistant — Population Data BC May 2023 – Sep 2025 • Appointed project lead for the provincial intake of the Canadian Longitudinal Study on Aging (CLSA), a novel, first-of-kind dataset from the Canadian Institutes of Health Research comprising 10,000+ variables, coordinating cross-functional validation, documentation, and integration • Led dataset management and data intakes on behalf of major institutional stewards including BC Cancer, Immigration, Refugees & Citizenship Canada (IRCC), and the H.E.L.P. initiative • Contributed to finalising the DAR 2.0, an updated data request platform used by health researchers across Canada, participating in UAT and stakeholder feedback cycles • Collaborated across units with data stewards, researchers, and policy professionals to improve analyst access to linked administrative health data Graduate Teaching Assistant (CPSC 100) — UBC Faculty of Science Aug 2025 – Present • Responsible for instruction and lab lesson design in introductory computing concepts for a large undergraduate cohort Teaching Fellow (PSYC 218) — UBC Faculty of Arts Jan – May 2024 • Awarded a graduate-level teaching role following a course grade of 98%, a position normally reserved for graduate students • Designed and delivered lectures on SPSS and core statistics topics (linear regression, ANOVA) to approximately 200 students Teaching Assistant (APSC 160) — UBC Faculty of Applied Science Sep – Dec 2023 • Assisted in teaching a 700+ student introductory C programming course covering documentation and electrical circuitry applications • Appointed Head TA during final exam invigilation; authored new exam questions testing intermediate skills in strings, functions, and algorithms Teaching Assistant (CPSC 100) — UBC Faculty of Science Jul – Sep 2023 • Hosted independent lab sessions, office hours, and tutoring for 200+ students in introductory programming and algorithmic problem-solving Research Assistant — UBC Social Cognition & Emotion Lab Apr – Sep 2023 • Collected and managed over 250 participant datasets; oversaw recruitment, debriefing, and study validity protocols under real-world conditions LEADERSHIP & COMMUNITY INVOLVEMENT Admissions Committee Member — UBC Master of Data Science Nov 2025 – Present • Reviewed and evaluated applicant submissions for the MDS programme as a student committee member Social Student Representative — UBC Master of Data Science Sep – Dec 2025 • Selected as one of six student representatives for MDS Cohort 10; responsible for community-building, social programming, and networking events • Organised a cohort hackathon and secured sponsorship from an AI research lab (CAIDA) Judge & Mentor — Women in Data Science @ UBC Oct – Nov 2024 • Evaluated 11 submissions across two rounds of the WiDS case competition, assessing model performance, data cleaning, and results communication • Mentored current UBC students at the WiDS Alumnight on networking, job applications, and data science career pathways Events Director — UBC Women in Data Science Club May 2023 – Jun 2024 • Planned and produced panel events featuring industry professionals from Google, Shopify, and Procter & Gamble • Secured sponsorships from local companies and founded a recurring alumni mentorship event VP Creative — UBC Dance Horizons May 2020 – May 2023 • Led creative direction and event production for a 20–50 member club; managed performance planning, content, and member coordination across three years VP Creative & Media — UBC Unlimited Dance Club Sep 2021 – May 2023 • Held simultaneous executive creative role across two clubs; coordinated overlapping event calendars and media production Provincial Page — Legislative Assembly of Ontario Mar – May 2013 • Served in the Ontario Legislature assisting Members of Provincial Parliament; present for and assisted in delivery of the 2013 Provincial Budget PROJECTS & COMPETITIONS Cursor AI Hackathon — Voxolith Feb 2026 • Built a full-stack, interactive 3D visualisation tool for complex neuro-spatial data using Python, Plotly, and Streamlit • Designed a dynamic frontend UI with hover-over tooltips and region-highlighting, bridging backend data with accessible user interfaces • Implemented stochastic data generation using FastNoise2 and Simplex noise functions, creating complex, non-linear environmental models for terrain synthesis. nwHacks 2026 — SightQuest Jan 2026 • Orchestrated a high-performance backend workflow to ingest and process multimodal data streams, utilizing Python to bridge raw sensory input with generative AI models • Integrated the Gemini 3 Pro API to perform zero-shot visual reasoning and complex task planning, enabling the system to interpret 3D environments and provide context-aware feedback. BOLT Datathon [Semi-Finalist] Oct 2025 • Sole data scientist and programmer; developed a pipeline to consolidate siloed datasets, comprising stadium attendance, membership tiers, and product purchases, using Pandas for complex joins and data cleaning to create a 360-degree customer view • Implemented a K-Means Clustering model to segment the fanbase into distinct behavioral personas, enabling targeted marketing and retention strategies. nwHacks 2024 — Biomedical Waste Management System [Track Winner] Jan 2024 • Designed a digital biomedical waste management system for hospital implementation; placed top 3 in the Environmental & Sustainability track BizInnovate — Pacific Conference on Artificial Intelligence [1st Place] Apr 2023 • Supported the business presentation of a machine learning model predicting regional water quality using geospatial survey data and satellite image feature extraction; placed 1st out of 18 teams UBC girlCode × Aritzia Hackathon Jan 2023 • Delivered an original front-end and UI/UX product case project within a 24-hour sprint

Multimodal pCR Prediction for Breast Cancer March 2026 National Canadian Medical Datathon 2026 (3rd Place) • Designed an end-to-end multimodal deep learning pipeline to predict pathologic complete response (pCR) in breast cancer patients undergoing Neoadjuvant Chemotherapy (NAC). • Engineered a computer vision workflow utilizing OpenCV to extract critical spatial biomarkers: nuclear density, edge complexity, and clump count, from high-resolution Whole Slide Images (WSIs). • Built and optimized a custom Keras neural network trained on a multimodal dataset of extracted digital pathology features and traditional clinical history, successfully outperforming tabular-only baseline models. • Achieved an overall predictive accuracy of 78%, balancing a 92% precision rate for complete responses with a 93% recall rate for partial responses to align with clinical triage needs.

CERTIFICATIONS TCPS 2: CORE — Tri-Council Policy Statement on Ethical Conduct for Research Involving Humans (Sep 2020)