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PAMELA KINGA @
THE BIG DATA LIFE
Big data trends | tools | services
Data Science
Data science is a multi-disciplinary function that combines expertise in mathematics and statistics, inference, and computer programming. Data scientists merge their skills to solve business problems in a specific domain.
Want to be
a data scientist?
"Data scientists realize that they face technical limitations, but they don’t allow that to bog down their search for novel solutions. As they make discoveries, they communicate what they’ve learned and suggest its implications for new business directions. Often they are creative in displaying information visually and making the patterns they find clear and compelling. They advise executives and product managers on the implications of the data for products, processes, and decisions." - HBR
What characterizes a data scientist?
"The dominant trait among data scientists is an intense curiosity—a desire to go beneath the surface of a problem, find the questions at its heart, and distill them into a very clear set of hypotheses that can be tested. This often entails the associative thinking that characterizes the most creative scientists in any field."
- HBR
Company shoutout: data science @ Airbnb
March Feature
Airbnb is the world's fastest growing accommodation-sharing site and is a premiere destination for data scientists in the field. In November 2016, the company launched Airbnb Experiences - an opportunity for expert hosts to offer handcrafted activities vetted by a team of editors who verified that experiences were worthwhile explorations into a city's local scene and culture.
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After growing the business to over 1,000 destinations, Airbnb used data science to optimize the user experience. A team of data scientists used machine learning to improve Search & Discoverability functions and Personalization of recommendations and bookings.
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Constrained by the lack of big data generated by the new service as well as working in both offline and online settings, the Experiences Search Ranking team deployed a variety of machine learning algorithms on training data sets ranging from 50K to 2Million data observations.
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For example, Airbnb was able to uncover that while visiting Paris, Japanese travelers prefered Classes & Workshops (e.g. Perfume making), US travelers prefered Food & Drink Experiences, while French travelers prefered History & Volunteering. They used this information to engineer several personalization features.
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For a complete review of the project check out Machine Learning-Powered Search Ranking of Airbnb Experiences.
Data Science Competitions
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