🌟the main missions are to:🌟
We are looking for a Data Scientist to help us accelerate the world transition to a more sustainable aviation through digital technologies.
You will apply machine learning algorithms and statistical techniques to build new product features in order to provide additional fuel-savings opportunities to our customers. A wide range of algorithms such as clustering, SVM, LSTM networks or robust linear regression are currently in use to tackle the technical challenges we’re facing in a pragmatic way.
In collaboration with product and engineering team members, you will be responsible for developing innovative and pragmatic algorithms to bring additional value to our customers.
At OpenAirlines, the data science team owns the development process of new features from end to end (from early discussions with pilots and fuel analysts to the development, deployment and monitoring of the chosen algorithm in production).
🌟 Activities & Responsibilities:🌟
• Apply machine learning algorithms and statistical techniques to build new product features.💻Technical stack:
• Understand and translate business needs into innovative new functionalities
• Design, put in production and monitor new algorithms to better track the application of fuel savings initiatives.
• Contribute to the improvement of the data science technical stack.
• Example of projects you might be able to work on:• Modeling of new fuel savings best practices.
• Flight data analysis (time series) to compute additional business indicators.
• Smart insights, helping our customers to dynamically identify improvements in their operationss
• Python, Java, SQL
• Pandas, PyTorch, Scikit-learn, ,…
• Git, Docker, Google Cloud Platform
🌟 Activities & Responsibilities:🌟
• Apply machine learning algorithms and statistical techniques to build new product features.💻Technical stack:
• Understand and translate business needs into innovative new functionalities
• Design, put in production and monitor new algorithms to better track the application of fuel savings initiatives.
• Contribute to the improvement of the data science technical stack.
• Example of projects you might be able to work on:• Modeling of new fuel savings best practices.
• Flight data analysis (time series) to compute additional business indicators.
• Smart insights, helping our customers to dynamically identify improvements in their operationss
• Python, Java, SQL
• Pandas, PyTorch, Scikit-learn, ,…
• Git, Docker, Google Cloud Platform
🌟Requirements & skills🌟
• At least 3 years of experience in a similar position.
• Master degree / PhD in a relevant field (Data Science, Statistics,…)
• Excellent analytical skills, including deep statistical and modeling knowledge, combined with great communication skills.
• Good understanding of software engineering best practices.
• High proficiency in python and its data science stack
• Fluent in English
🌟Salary & Conditions :🌟
• Salary: 40K€ - 45k€
• Training
• Remote-friendly
• Advantageous company mutual insurance
• 50% of the Tisseo pass is paid for
• Super pleasant offices near Capitole
• FedEx days, 24 hours to innovate, every quarter
• Incredible teambuildings
🌟Salary & Conditions :🌟
• Salary: 40K€ - 45k€
• Training
• Remote-friendly
• Advantageous company mutual insurance
• 50% of the Tisseo pass is paid for
• Super pleasant offices near Capitole
• FedEx days, 24 hours to innovate, every quarter
• Incredible teambuildings
Our hiring process:
1. 30 minutes phone interview with a member of the recruitment team: to discuss and understand your career plan and answer questions you may have.
2. Interview in our office or in remote with the manager & our the HR
3. A Technical use case : A remote exercice and after a meeting with the team to discuss about this test.
Our hiring process:
1. 30 minutes phone interview with a member of the recruitment team: to discuss and understand your career plan and answer questions you may have.
2. Interview in our office or in remote with the manager & our the HR
3. A Technical use case : A remote exercice and after a meeting with the team to discuss about this test.