Carpe Datum

• S4E11 Ann Hodgetts: Breaking the Science Stereotype

  Influence of a Secondary School Teacher: Early encouragement can lead to long-term impact of belief and representation in STEM.Problem-Solving Approach: Complex challenges are tackled through structured thinking, practical questioning, and a focus on clarity over complexity.Making STEM Accessible: STEM is made approachable by connecting concepts to everyday life, encouraging curiosity, and removing barriers of intimidation.Shift to STEMAZING and Inclusion: Transition into education and inclusion stemmed from a recognition of systemic gaps and a drive to increase representation in STEM fields.Link to Stemazing: https://www.stemazing.co.uk/Link to mentioned TedTalk: https://www.youtube.com/watch?v=_S4ZWYofAdQ

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• S4E10 Daisy Wu: Turning Data Into Decisions

  Mentoring at UofT: Helped students see hidden opportunities (like work-study programs), shaping a mentorship style grounded in practical guidance and empathy.Project Coordination at Canada Bread: Learned to simplify data communication by focusing on outcomes, not visuals but answering “So what?” for non-technical stakeholders.Adapting Across Projects: Staying curious and doing deep research into each domain helps turn unfamiliar territory into valuable insight.Taking a Career Break: Pausing my career to pursue an MBA at Yale was about growing into a strategist who connects data with business impact.

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• S4E9 Irene Jerry: Pliability, Flexibility, Bendability

  Supporting Teams & Embracing Challenges at Aize: Data solutions through collaboration and adaptability, ensuring they’re intuitive and aligned with user needs.NHIF Internship & Interest in Data Analytics: NHIF spark to explore data’s role in healthcare, blending purpose with problem-solving.Teaching Diverse Learners in STEM: Adapting content with pliability, switching methods and tools based on each student’s exposure level.Mentorship Impact in STEM: Bridging the gap with coding and actively pursuing a CS path.

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• S4E8 Kristin Tsui: Research Meets Real World

  Short Intensive Courses (e.g. Kaggle x Google Gen AI): Short intensives give you concentrated exposure and momentum for testing new skills quickly without a long commitment.Breaking Into Data Science Without a Formal Background: Credibility comes from consistency like personal projects and public contributions.Overlaps Between Draco Work and Academic Research: Even across different domains, problem-solving patterns, experimental design, and data fluency often connect the dots unexpectedly.Most Rewarding Part of Life Science Research Role at Stanford: The dual impact of advancing human health while constantly learning.

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• S4E7 Nandita Krishnan: Human Side of STEM

  Consulting to Data Science: Structured thinking and stakeholder empathy are just as critical in data science as they are in consulting.Choosing Tools in Evolving Environments: Letting the problem dictate the method.Mentoring vs. Judging at Hackathons:The key is timing to guide with empathy, clarity, and fairness during and at the end of the process.Personal Interests Shaping Professional Identity: Integrating personal passions into professional life makes your work more authentic, relatable, and impactful.

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