Hilary Mason Quotes

Powerful Hilary Mason for Daily Growth

About Hilary Mason

Hilary Mason (born March 18, 1984) is an influential American data scientist, entrepreneur, and public speaker renowned for her work in artificial intelligence, machine learning, and data-driven decision making. Born and raised in San Francisco Bay Area, California, Mason's passion for technology was sparked at a young age. She earned her Bachelor of Science degree in Symbolic Systems from Stanford University, where she focused on computer science, cognitive science, and linguistics. Her academic background provided a strong foundation for her future work in data analysis and machine learning. Mason began her career as a data scientist at various tech companies, including Bitly, and was the first data scientist at Bit.ly, where she helped improve the platform's analytics capabilities. In 2010, she co-founded and served as the Chief Scientist for Rapleaf (later known as fullcontact.com), a big data company that provided solutions for identity resolution and verification. In 2013, Mason moved to Accel, where she led the new research and partnerships division, working closely with startups in the machine learning space. She later joined Google as the Head of Machine Learning and Data Science for Google X, developing artificial intelligence and machine learning solutions for various projects. Aside from her corporate work, Mason is a frequent public speaker and writer on topics related to data science, AI ethics, and diversity in technology. In 2016, she published "Data Scientist's Toolkit: Essential Skills for Working with Data," offering practical advice for data practitioners. Hilary Mason continues to be a prominent figure in the tech industry, advocating for responsible AI, mentoring underrepresented groups in technology, and pushing the boundaries of what can be achieved through machine learning and data science.

Interpretations of Popular Quotes

"Data is like garbage: you have to sort it out before you can use it."

This quote emphasizes the importance of data cleaning and organization in data analysis, just as one must clean and sort through garbage before using it for a useful purpose. The implication is that raw data often contains inconsistencies, errors, and redundancies that must be addressed before it can be utilized effectively to derive insights or make informed decisions.


"The world isn't just numbers; the world is stories waiting to be told through those numbers."

This quote emphasizes that data, or numbers, are more than just cold statistics; they are rich narratives containing insights about our world. By telling the stories behind the data, we can uncover hidden patterns, trends, and meaning, ultimately shedding light on the human experiences and events that shape our societies and cultures. In essence, Mason is suggesting that if we want to truly understand the world, we must learn to interpret the stories that lie within the data.


"Machine learning is like raising a child – you have to start with a lot of hand-holding, but if you do it right, eventually you can set them loose on their own and they will amaze you with what they can learn."

This quote by Hilary Mason compares the process of training a machine learning model to raising a child. The initial stages require extensive guidance (hand-holding) to establish foundational knowledge and parameters, similar to teaching basic skills to a child. However, as the model matures, it should ideally become independent, capable of learning and making decisions on its own, just like a well-raised child can make wise choices based on their upbringing and education. The "amazement" mentioned in the quote refers to the unexpected insights or discoveries that such an autonomous model may generate through its self-learning process, mirroring the awe-inspiring achievements of grown children who've developed their unique talents and abilities.


"If you're not in the habit of looking for patterns, it's easy to miss them when they're staring you in the face."

This quote emphasizes the importance of pattern recognition and analysis, suggesting that our ability to identify trends, correlations, or recurring events, impacts our understanding of the world around us. Often, these patterns can provide valuable insights about underlying phenomena, yet they may go unnoticed if we are not accustomed to seeking them out. This underscores the significance of cultivating a habit of observation and analysis in various aspects of life, as it enables us to make better-informed decisions and gain deeper understanding.


"Data science is a team sport – it takes people from many disciplines to make sense of data and put it into action."

This quote by Hilary Mason highlights the collaborative nature of data science, emphasizing that diverse skills are essential for deriving meaningful insights from data and effectively applying them in real-world scenarios. By drawing upon different disciplines such as mathematics, statistics, computer programming, business, and communication, a team can tackle complex data problems more efficiently, ensuring accurate results and actionable insights. This interdisciplinary approach allows for a more comprehensive understanding of the data being analyzed and fosters innovative solutions that address both technical and practical challenges.


In tech entrepreneurship, even a lot of hack events tend to be overly commercial in that they're designed to produce companies.

- Hilary Mason

Commercial, Tech, Produce, Overly

I think e-mail should be sorted by importance, not by time.

- Hilary Mason

Think, I Think, Importance, Sorted

Deep learning allows you to create predictive models at a level of quality and sophistication that was previously out of reach. And so deep learning also enhances the product function of data science because it can generate new product opportunities.

- Hilary Mason

Deep, New, Models, Predictive

My job is to analyze our data set to understand it and build products on it. I look at raw data, do the math to clean it up, and build systems to make it easy to understand.

- Hilary Mason

Data, Understand, Set, Analyze

I'm a huge fan of the liberal arts approach of teaching you to think, analyze, and communicate, then sending you out into the world to cause trouble.

- Hilary Mason

Think, Liberal Arts, Cause, Analyze

Cool innovation might happen in startups, but they often lack the resources or the deep expertise in the problems they want to address.

- Hilary Mason

Innovation, Deep, Happen, Startups

Companies that rely on licensing a proprietary dataset should expect to be outpaced by competitors using modern data collection techniques and more frequent updates and greater accuracy.

- Hilary Mason

Data, More, Using, Proprietary

After graduate school, I joined Johnson & Wales University in Rhode Island as an assistant professor, but I continued to program in addition to teaching and working on research. I built a program that crawled job boards to determine which skills employers value, which helped Johnson & Wales explore ways to improve its curriculum.

- Hilary Mason

University, Teaching, Boards, Graduate School

If you find something obscure fascinating, learn as much about it as you can, because there's a good chance it won't be obscure for long.

- Hilary Mason

Chance, Learn, About, Good Chance

When you start at Bitly, you go through this emotional cycle, where first you go, 'Oh my God, this data is amazing.' But then you start looking at it, and you conclude that humanity is completely doomed. Because what people read is cats and Bieber and celebrity gossip and that stuff.

- Hilary Mason

Data, Celebrity, Through, Doomed

The sender and subject line are actually the most important parts of an e-mail because people tend to put more important information in the subject.

- Hilary Mason

The Most Important, Line, E-Mail

I'm really curious about people - what their desires and interests are - and bit.ly's data tell me that. It gives me an unprecedented window into human communication and behavior.

- Hilary Mason

Curious, Data, Desires, Unprecedented

I wish I'd known more about how to build a startup when I was younger.

- Hilary Mason

Wish, How, I Wish, Startup

A good scientist can understand the current state of a field, pick interesting questions where a success will actually lead to useful new knowledge, and push that field further through their work.

- Hilary Mason

New, Will, Through, New Knowledge

Often, people think that individual data is the most valuable thing they can collect. But it's not useful to know what I am doing or where I am, unless you're particularly interested in me, which is weird. But it is very useful to know what a population of people are doing.

- Hilary Mason

Doing, Data, Very, Collect

Teaching someone to program is like giving them a superpower.

- Hilary Mason

Someone, Like, Teaching, Superpower

You really need to have a lot of empathy for the work you're doing and the people who you're ultimately trying to help, whether that's a business colleague, a boss, or, ultimately, the user of the software you're building.

- Hilary Mason

Empathy, Boss, Doing, Colleague

I don't actually, as a general policy, block any sort of cookies. I keep them all turned on, and that's because I'm willing to make the tradeoff that I let companies gather this information about me in return for a better experience.

- Hilary Mason

Willing, About, Turned, Block

I think of 'data science' as a flag that was planted at the intersection of several different disciplines that have not always existed in the same place. Statistics, computer science, domain expertise, and what I usually call 'hacking,' though I don't mean the 'evil' kind of hacking.

- Hilary Mason

Data, Flag, I Think, Intersection

Data is a tool for enhancing intuition.

- Hilary Mason

Data, Intuition, Enhancing, Tool

I hope that, in the future, data is used to empower people and not just for marketing purposes.

- Hilary Mason

Future, Marketing, Data, Purposes

I joined bit.ly as chief scientist in October of 2009. The company is a URL-shortener and content-sharing platform; we provide tools for people to share and track links on the Internet.

- Hilary Mason

Chief, Scientist, Joined, October

Don't be afraid to push your company in the direction you think is right - you'll either be fired or promoted, and either outcome will end up just fine.

- Hilary Mason

Think, Will, Fired, Outcome

Nobody really cares about short links, but people do care about saving and sharing content.

- Hilary Mason

Cares, About, Saving, Sharing

Technology is giving companies superpowers to compete more intelligently and capture the data behind changing trends, expanding markets, and new opportunities.

- Hilary Mason

Compete, New Opportunities, Trends

My Grinnell education didn't prepare me directly for the work that I'm doing, but it did give me the tools that I needed to focus my curiosity.

- Hilary Mason

Doing, Give, Prepare, Give Me

A lot of people seem to think that data science is just a process of adding up a bunch of data and looking at the results, but that's actually not at all what the process is.

- Hilary Mason

Process, Data, Think, Adding

Data science is the combination of analytics and the development of new algorithms.

- Hilary Mason

Development, Data, New, Combination

It's easy to find people who can make pretty pictures, and it's easy to find people who can do math. But it's difficult to find people who can do both.

- Hilary Mason

Find, Pretty, Difficult, Math

Value experiences by how much you're learning, and if you're aren't learning, move on.

- Hilary Mason

How, Move, How Much, Move On

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