class DiyaSaxena:
    def __init__(self):
        self.education = "University of Waterloo"
        self.program = "CS + Finance"
        self.current_role = "Technical PM Intern @ FSRA"
        self.highlight_role = "Sponsorship Coordinator @ Hack the North"
        self.based_in = ["Toronto", "Waterloo"]
        self.work_authorization = ["United States", "Canada"]

    def interests(self):
        return [
            "FinTech",
            "Quantitative Finance",
            "Data Analysis",
            "Backend Systems",
            "Machine Learning",
        ]

    def currently(self):
        return {
            "building": "RaceIQ — an F1 strategy intelligence platform",
            "exploring": "financial systems, data, and software",
            "open_to": "interesting convos, projects, and opportunities",
        }

• I like taking broad or messy questions and turning them into something useful.
• Most of my projects live somewhere between finance, data, and software.
• I am currently interning as a Technical PM at FSRA.
• I enjoy learning how systems work, testing ideas, and building with people who care about the details.

I spend time on both sides of hackathons: building projects and helping make the events happen.

• Hack the North — Sponsorship Coordinator: helping organize the event by working with sponsors, coordinating partnerships, and supporting the experience behind the scenes.
• CxC — Sponsorship: organized sponsorship for an AI-focused hackathon.
• DeltaHacks 12 — Hacker: attended and built MediMonitor with my team.
• ChessHacks — Hacker: built [or more like tried to build] a chess bot to beat all other bots.

• Python for data, automation, finance projects, and machine learning
• Java and C for programming fundamentals and lower-level problem solving
• TypeScript for web applications and backend work
• SQL for working with structured data
• Git for version control and collaboration

• Cleaning and exploring data with Pandas
• Numerical modelling and optimization with NumPy
• Training and evaluating models with scikit-learn
• Creating visual explanations with Matplotlib
• Prototyping analysis in Jupyter
• Working with financial-market data through yfinance

• Currently building an interactive F1 strategy intelligence platform
• Developing a Pit Now vs. Stay Out model using tyre data, stint information, and race conditions
• Building the dashboard, backend API, and machine learning pipeline

• Built a quantitative portfolio optimization project
• Tested different allocations under risk and return constraints
• Explored how optimization methods could improve portfolio construction

• Compared Shopify shares listed on the TSX and NYSE
• Accounted for currency conversion and cross-border pricing differences
• Explored when an apparent arbitrage opportunity was actually worth acting on

• Built a healthcare application focused on monitoring patient information and health signals
• Worked on making complex health data easier to understand and act on

• Interning as a Technical PM at FSRA
• Organizing Hack the North as a Sponsorship Coordinator
• Studying Computing & Financial Management at the University of Waterloo
• Building projects across fintech, data, machine learning, and software
• Based between Toronto and Waterloo, Ontario
• Interested in internships across fintech, quant, data, and software engineering
• Open to opportunities across Canada and the United States

I am always happy to meet people working on thoughtful problems in finance, data, software, or the hackathon community.