#314 How to Have a Career in Data Science in 2025 with Dawn Choo, Data Careers Influencer, Co-Founder at Interview Master

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Aug 11, 2025

Dawn Choo, Co-Founder of Interview Master and an experienced data strategist, discusses the evolving landscape of data science in the age of AI. She highlights that generative AI is creating more demand for data professionals instead of replacing them. Dawn emphasizes the importance of adapting skills, balancing traditional techniques with AI advancements, and mastering communication for career success. She also explores emerging roles in the data field, offering practical tips for candidates navigating interviews and emphasizing the continuous learning journey.

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ADVICE

Master Technical And Soft Skill Triad

Learn SQL and Python plus foundational statistics and basic machine learning models like regression and decision trees.
Also develop product sense and clear communication; these soft skills weigh heavily in hiring.

ADVICE

Build A Portfolio Early, Show Impact Later

Early-career candidates must build a portfolio of projects showing code, analysis, and outcomes.
Mid-career candidates should present quantified strategic, operational, and infrastructure impacts from work.

ADVICE

Quantify Outcomes Or Scope To Show Impact

Prefer measuring your impact by business outcomes like revenue, conversion, or cost reduction.
If you cannot measure outcomes, quantify scope such as managed revenue or number of data sources.

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Data science continues to evolve in the age of AI, but is it still the 'sexiest job of the 21st century'? While generative AI has transformed the landscape, it hasn't replaced data scientists—instead, it's created more demand for their skills. Data professionals now incorporate AI into their workflows to boost efficiency, analyze data faster, and communicate insights more effectively. But with these technological advances come questions: How should you adapt your skills to stay relevant? What's the right balance between traditional data science techniques and new AI capabilities? And as roles like analytics engineer and machine learning engineer emerge, how do you position yourself for success in this rapidly changing field?

Dawn Choo is the Co-Founder of Interview Master, a platform designed to streamline technical interview preparation. With a foundation in data science, financial analysis, and product strategy, she brings a cross-disciplinary lens to building data-driven tools that improve hiring outcomes. Her career spans roles at leading tech firms, including ClassDojo, Patreon, and Instagram, where she delivered insights to support product development and user engagement.

Earlier, Dawn held analytical and engineering positions at Amazon and Bank of America, focusing on business intelligence, financial modeling, and risk analysis. She began her career at Facebook as a marketing analyst and continues to be a visible figure in the data science community—offering practical guidance to job seekers navigating technical interviews and career transitions.

In the episode, Richie and Dawn explore the evolving role of data scientists in the age of AI, the impact of generative AI on workflows, the importance of foundational skills, and the nuances of the hiring process in data science. They also discuss the integration of AI in products and the future of personalized AI models, and much more.

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