We’re creating a more connected travel industry, underpinned by sustainability and long-term investor relations.
Data Scientist, Travel Intelligence, Amadeus IT Group
Editor’s note: It’s been labelled the sexiest profession of the 21st Century, one where demand has raced ahead of supply, a hybrid of data hacker, analyst, communicator, and trusted advisor. Data Scientists are people with the skill set (and the mind-set) to tame Big Data technologies and put them to good use. But what kind of person does this? Who has that powerful –and rare- combination of skills? In this series, Amadeus’ team of Data Scientists seek to unlock the answers to those questions and their impact on travel.
10 unknown facts
1. Data scientists are in demand
We are in the middle of a data revolution which has brought along an endless flow of unmined information. The management of this data is critical for companies in all areas, from insurance and media to travel & tourism as new opportunities arise for those who can see them. Data scientists are needed to help manage these massive data volumes and turn them into useful, actionable information.
2. Data scientists find hidden value in data
Say you want to join a team of data scientists. Have you considered that you will need to take care of a huge volume of information coming from multiple sources and glorify it ? A data scientist should be able to see business value in raw data and detect any possible error that could ruin the outcome. For instance, we can define and develop the best algorithm to find increasing or decreasing airline routes in terms of numbers of passengers, but if we forget to check (and re-check) the referential data we will lose all the value of our work. Only a true passion for data will push you to treat the data as is required.
3. Data scientists look at past data in detail
A data scientist learns lessons from the past in order to predict the future. For example, airlines can use historical data around demand for a particular route to adjust flight capacity and price in order to maximize benefits.
4. A data scientist has to be creative
Technical skills and a love for data are important, but not enough. A data scientist must also be creative in order to make the data speak and get leads from specific indicators. The next step after using data to obtain information is to turn that information into visuals to make messages clearer and more memorable.
5. A data scientist can tell stories with data
Visualization is a good way to communicate findings, but data scientists use an additional tool: stories. A data scientist sees stories and trends where other people only see unintelligible raw data. A data scientist brings the data to life just as a good narrator makes his story come alive.
6. Yes, there are female data scientists
A data scientist should have a deep technical background to be able to tackle the data. Indeed, we have to deal with “small” data sets (e.g. 20,000 lines in a CSV for the Points of Reference data ) but also large data sets (e.g. 40 GB/day of raw data for Search Analysis). That’s why a logical mind as well as mathematics and computer skills are required: a data scientist should be a geek! Many think that most data scientists would be male as a result. However, a data scientist position also attracts females. There are two women and four men in my office: not so bad in the computer world!
7. A data scientist is an explorer
Data scientists have to dig deep into data in order to mine precious knowledge. But they have to be careful and avoid “traps” due to errors in data. Data scientists are explorers, but must also be rigorous.
8. A data scientist should be curious
A data scientist is always looking for new approaches, new methods and new business knowledge in order to improve his/her technical and functional skills. Curiosity is a critical quality in a data scientist. For instance, some analyses give a lot ofoutliers: why? Is there an error in the data? Is this an indicator of a particular trend?
9. The perfect data scientist is a team
So you think that you have all the qualities required to be a good data scientist? Don’t forget that data scientists work best in a team. A data scientist cannot be the best everywhere and every time. That’s why a data scientist should also be good team player. We help each other in order to save time and learn from each other to improve our skills.
10. Data scientists love sharing knowledge
Indeed, as all good team players, data scientists like to share knowledge. In fact, this is partly the basis of our work: turning raw data into valuable information in order to share it!