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Data Science vs. Statistics: Demystifying Tech Careers

Thinking about tech careers that involve data? Data Science and Statistics might sound similar, but they have distinct roles. Let's break it down!

Data Science: Data scientists are the ultimate data wranglers. They gather and clean different types of data, not just numbers. They use their coding skills and analytical tools to identify patterns and trends hidden within the data. Their goal? To extract insights and present them in a clear way for everyone to understand. Think of them as the information architects, building a clear picture from raw data.

Statistics: Statisticians are the data relationship experts. They use complex mathematical models to analyze connections between different data points. Their focus is on understanding how these data points influence each other and predict future outcomes. While they may use some algorithms, they don't rely heavily on machine learning like data scientists. Imagine them as the data detectives, uncovering the "why" behind the data.

Watch the full video to learn more about these tech careers!
#datascience #statistics #techcareers #careeradvice

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Hi, I'm Jean, Founder of Exaltitude. I've been working in tech for the past 20 years as an engineer, an engineering manager, and a team builder. I was the 19th engineer at WhatsApp and worked with Facebook as an Engineering Manager for six years after the $19B acquisition. I'm excited to share the ins and outs of a Software Engineering career based on my experience as a hiring manager for top tech companies.


Credits
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🖼️ All images, graphics, and b-roll videos used in this video were sourced from Canva.

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