Skyscanner
Role Profile
Position:
Principal Data Scientist, Hotels
Location:
Barcelona
About the Role:
Role Overview
As part of Skyscanner´s mission of creating the best travel search engine,
Skyscanner is expanding its Barcelona team who developed the recently launched
Skyscanner hotel search service.
Skyscanner has a large number of users and there´s huge upside in using data
science methods to optimize 1) the user experience (showing users the optimal
results for their search, effectively personalizing them to their needs), 2) the
monetization of the service (using historical conversion and revenue data to predict
the configuration that will optimize our revenue), 3) the marketing of the service
(identifying which user segments are more profitable for the business and trying to
acquire more users of these segments) and 4) the user retention of the service
(identifying the churn probability of different customer segments and activating
lifecycle marketing actions targeted to these customer segments).
As the principal data scientist for Skyscanner Hotels, your responsibility will be
using available data to improve our products, the overall customer experience and
the profitability of the business.
This is a hands on role, where you´ll be able to make end-to-end changes to our
products, from the analysis of the data and the creation of predictive models to the
engineering of the final solutions, the A/B testing and deployment in production.
In addition, the expectation is that you´ll be proactive in finding improvements, that
is, you´ll dig into the data and propose improvements to all relevant stakeholders in
the business.
Core
Responsibilities:
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Working with large-scale, complex behavioural, marketing and revenue data to
help us better understand our customers and discover patterns within our
business.
Generating improvement proposals based on data across all areas (product,
monetization, marketing, etc).
Developing customer lifetime value predictive models using statistical and
machine learning techniques to help us optimize acquisition and reduce churn.
Designing, creating and implementing algorithms and predictive models that
improve the user experience or the monetization and deploying them into
production.
Helping in the implementation of data-driven product features.
Producing reports and data visualizations that help other stakeholders make
decisions in key business areas.
Budget
Responsibilities:
No. of Direct Reports:
N/A
N/A
About the Department:
Reports to:
Senior Engineering Manager, Hotels
Department Structure:
(Team Description)
In Skyscanner Hotels we like to work in small, very efficient, agile teams that own a
relevant part or component of our platform. We use a mix of PHP, Python, Twisted,
Java, PostgreSQL, Hadoop, SOLR/Lucene, Couchbase, all on top of a Linux-based
infrastructure
We are a user oriented team. For us, software engineering is all about solving
problems for the users of our service, and therefore we are looking for candidates
that are passionate about internet businesses, have empathy for the end user and
are deeply interested in creating a world-class hotels product.
We are a data driven team. We continuously run tests with real customers to
measure the effect of new features and ideas, and therefore we are looking for
candidates that are focused not only in creating great software, but have both the
creativity and the interest in coming up with new ideas that improve our service and
move our key metrics forward.
We are a real time team. We believe in continuously pushing new software into
production and testing whether an idea works or not as fast as we can. Therefore,
we are looking for very active candidates that enjoy the thrill of being in always-on
mode, have a bias towards action, have a great idea/code ratio and can ship good
software under tight deadlines.
About You:
Personal Attributes
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You love coding and technology at large. Ideally you are the kind of person that
started programming at a very young age and for you coding is your passion,
and not just “work”.
You should be curious about the world at large and enjoy taking things apart to
find out how they work and improve them.
You should have a strong commercial focus and empathy for the end user.
You love data science and research but you are very practical and focused on
improving our product and business.
You are very hands on and you have a bias towards action and delivery of
solutions in production.
You have great communication skills.
You are very attentive to detail, yet pragmatic.
You are motivated by hard technical and scientific challenges.
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MSc or PhD in Comp Science, Math, Statistics, Machine Learning or similar.
Data driven and with a very strong quantitative background. Deep applied
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Qualifications:
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Required Skills and
Experience
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Optional Skills and
Experience
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Language(s):
math/statistics knowledge.
Very strong in data science applied to the optimization of an internet
business, with demonstrable impact. Minimum 7 years experience in a
similar positions, working on highly trafficked, international, large internet
companies. Experience in e-commerce and/or online travel companies will be
valuable but not mandatory.
Extraordinary breadth in statistical modelling, data mining and machine
learning. Very experienced in solving many different problem types
(classification, regression, prediction, etc) and very articulate in making
decisions on the best models, algorithms and tools for solving each business
problem. Substantial practical experience with most of the relevant machine
learning and data mining algorithms.
Extraordinary depth in statistical modelling data mining and machine learning.
You have very strong experience in troubleshooting the low-level issues of
deploying and maintaining large-scale statistical models in production
environments (problems with the data, buggy implementations of machine
learning algorithms, etc).
Strong hands on experience designing, implementing and maintaining
production-level predictive models using state of the art machine learning and
data mining algorithms and tools.
Experience in creating and deploying production-level customer lifetime value
predictive models in large-scale environments.
Strong hands on experience with statistic suites/languages (R, etc) and modern
data visualization / BI software (Tableau, Cognos, Pentaho, etc)
High proficiency in Python and Java.
High proficiency in relational / analytic databases.
Experience in large-scale data processing techniques (filtering, dimensionality
reduction, noise reduction, etc) and tools (Hadoop or other distributed
computation systems)
Knowledge of predictive modelling applied to internet marketing will be highly
beneficial.
Experience in one or more of the following fields will be highly valued:
combinatorial optimization, quantitative trading, internet traffic bidding, yield
optimization, recommendation systems and/or ad serving optimization.
High scores in relevant data science competitions will be valued.
Experience in managing and mentoring a small team of engineers or data
scientists will be valued.
Essential: Fluent English
Desirable: Fluent Spanish
About Skyscanner:
Skyscanner is a world leading global travel search site providing instant online comparisons on millions of
flight prices on 1000 airlines, as well as car hire, hotels and holidays. The site is no.1 in Europe and no.3
worldwide and is increasing global market share rapidly.
Headquartered in Edinburgh UK, with other offices in Glasgow, Singapore, Beijing, Miami and Barcelona,
Skyscanner is a global business – the site is available in more than 30 languages and has significant market
presence in over 40 countries worldwide.
With more than 25 million visitors to the Skyscanner sites each month – 50% of which are repeat visitors –
and over 12 million app installations across iOS, Android and Windows Phone since launching in 2011,
Skyscanner is growing rapidly, generating around $3 billion of revenue in the last year for client airlines and
online travel agents.
Unlike other travel sites, Skyscanner combines intelligent technology and data from hundreds of independent
flight price sources to create a search experience that adapts to how our customer wants to search for travel.
Customers can search using specific dates and destinations, or by airport, city, country, month or year.
Skyscanner is also a powerful tool for travel inspiration; users can search from any destination to
‘everywhere’ to see their cheapest flight options.