Isabela Lucas

As Founder and Managing Director of Sinnux, I focus on aligning business strategy with the systems that support it. We begin by working closely with leadership teams to understand operational challenges, growth goals, and structural gaps. From there, we define a clear roadmap for modernizing and strengthening core business systems. Sinnux is not a strategy-only consultancy. We design and deliver the systems required to execute. That includes custom software, workflow automation, and fully integrated operational platforms tailored to how each organization actually runs. I lead the direction and oversight of every engagement from initial assessment through implementation, ensuring that what we build is not just technically sound but strategically aligned. Our work is centred on reducing operational friction, improving visibility, and creating infrastructure that supports long-term growth. The goal is simple. Build systems that move with the business instead of holding it back.

At UBC’s Office of Enterprise Risk and Assurance, I apply advanced data analytics and AI-driven automation to enhance risk management, internal audit, and investigations, boosting efficiency, accuracy, and insight. This includes: - Providing strategic leadership by aligning technology initiatives with organizational goals and long-term vision, delivering scalable, resilient solutions that embed innovation into core risk and audit functions. - Developing custom tools and applications using Python, React, and SQL, including the end-to-end design and implementation of the ERA Application Hub—a user-friendly platform that enables non-technical stakeholders to access and utilize internally developed tools such as web scrapers, AI-enabled functionalities (via APIs), and automation scripts, thereby strengthening and automating workflows. - Driving technology transformation by designing, piloting, and deploying advanced AI solutions that integrate complex workflows, natural language processing (NLP), and prompt engineering to tailor AI outputs for audit and risk analysis—optimizing data extraction and insight generation from both structured and unstructured data. - Designing and managing complex data pipelines and building interactive dashboards and visualizations with Power BI, SQL, DAX, and Python, translating data into actionable insights and clear narratives for senior leadership, the board, and stakeholders. - Developing data governance frameworks, establishing data quality standards, authoring analytics policies, and fostering a culture of digital literacy and continuous improvement.

- Developed enhanced mapping logic and standardized protocols for configuring Standing Settlement Instructions (SSIs) across non-loan-enabled accounts. Collaborated with the Order Management System (OMS) development team to add critical data fields, streamlining the SSI setup workflow. - Authored comprehensive process documentation and detailed task guidelines for fund administrators, ensuring consistent adherence to operational standards and regulatory compliance. - Designed and implemented interactive Power BI dashboards to monitor KPIs and perform cross-database validations. Partnered with OMS developers to automate data refresh cycles and standardize datasets previously maintained manually. - Engineered a complex FX trade reconciliation process in DUCO, effectively resolving discrepancies caused by inconsistent data formats across multiple sources. - Created detailed visual process maps depicting key investment operations workflows, including the entire trade lifecycle and FX trade settlement procedures. - Received thorough training in non-loan settlements, portfolio compliance, corporate actions, collateral management, trade activity management, reconciliation (trade, cash, position), post-trade processing, derivatives operations, fails management, and compliance monitoring. - Trained a rotational intern on fundamental investment control functions, facilitating effective knowledge transfer and improving onboarding efficiency. - Participated in cross-functional reviews with 18 operational and investment teams, gaining extensive exposure to the full spectrum of investment operations.

- Developed dynamic Power BI dashboards leveraging advanced DAX calculations and SQL-based data modelling to support audit reporting, fraud forecasting, performance analysis, and decision-rule optimization, following data visualization best practices to enhance interpretability. - Contributed to the development of a Python-based machine learning model for cheque fraud detection, focusing on the identification of behavioural patterns and high-risk attributes. - Automated daily management workflows and reporting processes using VBA macros, reducing manual effort by over 50%, improving data accuracy, and enabling the team to focus on higher-value analytical tasks. - Actively engaged in Agile development processes, participating in stand-ups, sprint reviews, and planning sessions, gaining hands-on experience with iterative product delivery and cross-functional collaboration. - Collaborated with international, bilingual (Spanish-English) stakeholders across Analytics, Strategy, Payments, and Governance teams, contributing to fraud risk assessments for global initiatives and supporting the definition of mitigation requirements for implementation.

Political Economics Undergraduate Research Assistant to VSE professor Claudio Ferraz, Scientific Co-Director of J-Pal Latin America & Caribbean and Political Economy Network of LACEA. - Developed a Python-based OCR pipeline to digitize hand-written historical documents, eliminating manual transcription and accelerating data processing for large archival datasets. - Built an automated web scraping and crawling tool using Python and Selenium to extract structured data from hundreds of dynamically generated government web pages, enabling comparative analysis of historical election results across municipalities. - Conducted research on historical public policies and applied exploratory data analysis to assess the effects of education expansion and female enfranchisement on voting patterns, contributing to a study examining the long-term impact of political power concentration on economic development.

- Analyzed statistical models and nowcasting techniques applied to government-released Covid-19 data, generating semi-weekly analytical reports that informed public health policy discussions. - Managed a WordPress-based online platform, publishing daily updates, statistical reports, and media coverage to ensure timely and accurate public dissemination of research findings. - Computed regional-level metrics using advanced Excel and transformed raw data into digestible visualizations and insights for internal health reporting and research newsletters. https://covid19analytics.com.br/quem-somos/

- Conducted in-depth research on ESG frameworks and intangible asset valuation models, producing a comparative analysis of metrics most applicable to the mining industry. Identified key indicators across environmental impact, social responsibility, and governance to assess relevance and ROI potential. - Extracted and analyzed financial performance data using advanced Excel and R to benchmark Wenco’s ROI on intangible assets against major industry competitors, highlighting gaps and opportunities. - Developed a data-driven business improvement proposal to enhance the company’s ESG and intangible asset performance, which was presented to senior executives, initiating a cross-functional initiative to align sustainability goals with corporate strategy. - Synthesized findings into strategic insights and visual reports for leadership, contributing to long-term planning around sustainable innovation and socially conscious value creation.

- Completed a highly selective program with an acceptance rate under 4%, integrating rigorous coursework in economics, finance, and mathematics from the Vancouver School of Economics and UBC Sauder School of Business. - Developed strong quantitative and analytical skills through advanced courses such as Calculus I–III, Matrix Algebra, Empirical Methods, and Econometrics, enabling data-driven economic analysis and modeling. - Gained a solid foundation in economic theory and financial principles with Intermediate Microeconomics and Macroeconomics, Financial Accounting, Cost-Benefit Analysis, and Investment Theory. Emphasized practical application of economic methods for policy evaluation, market analysis, and investment decision-making.

- Completed a rigorous minor combining advanced programming, mathematics, and applied statistics to support data-driven decision-making. - Developed a strong computational and analytical foundation through coursework in data science methods, statistical modeling, and algorithmic thinking, with an emphasis on building reproducible, trustworthy analytical workflows that ensure transparency and consistency across projects.