Machine Learning Scientist

**Company Description**

We are looking for a Machine Learning Scientist to join our team of around 1,700 people worldwide to help us power up the travelers' journey for millions of h olidaymakers. If you are a motivated machine learning scientist who loves to work with challenging real-world problems on big data, keep reading, as you might be the perfect fit for this job.

Job Title - Machine Learning Scientist
Working model - Full remote in Spain
Team - You will join the Strategic Analytics team in the Technology department.
Level - Professional
Location - Spain
Contract - Permanent - full-time (36 h/week)

What your impact will be:

- Develop real-time machine learning solutions to deal with challenging real-world problems on big data
- Develop Ranking Algorithms based on deep learning
- Collaborate in a cross-functional team, including machine learning scientists, software engineers, machine learning engineers, and project managers

**Qualifications**
Your expertise:

- A Ph.D. in Computer Science, Mathematics, or Physics, or a Master's degree with a minimum of 3 years of experience in machine learning.
- Excellent knowledge of Supervised methods (Classification, Regression) and Unsupervised methods (Clustering, Feature Selection, Dimensionality Reduction)
- Good knowledge of Python and SQL, with knowledge of the most important Python libraries for Machine Learning and Data Analysis (scikit-learn, Pandas, matplotlib, Numpy, Scipy, MLflow)
- Experience with Deep Learning (Recurrent Neural Networks, Convolutional Neural Networks, and Autoencoders)
- Experience with Keras (and TensorFlow) or PyTorch

Desirable:

- Experience in Uncertainty Estimation (Monte Carlo Dropout, Deep Ensembles)
- Able to find creative solutions to interesting problems
- Curious with a constant desire to learn and collaborate

**Additional Information** Perks of working with us**:
**How we work together**:

- An inclusive, friendly, and international environment (you’ll be working with colleagues from +10 countries and over 48 nationalities)
- Shorter working week, with a half working day on Fridays
- Flexible start and end of the working day
- Possibility to work from anywhere for a period of time per year defined according to local regulations

**How we learn together**:

- Fri-Yays: half a day on Friday morning with a no-meeting mandate and dedicated to deep work, personal growth, learning and training and/or focus time.
- Professional and managerial skills development training paths, access to e-learning platforms such as O'Reilly, Udemy, Coursera (depending on the department), and to our internal platform offering bespoke training content

**Other perks**:

- 2 paid days off per year for volunteering purposes
- Occasional social events to foster connections among colleagues
- Travel industry discounts and flash exclusive staff fares
- We support our employees through life's significant moments with leave options (e.g parental responsibilities, marriages, bereavements, relocations, etc.) in line with local laws.

Wish you were here? We do, too

**Selection process steps**:

- HR interview (30 minutes)
- 1st interview (Manager 1 hour): Machine learning + Python coding
- 2nd interview (Director 45 min): Soft skills +**machine learning knowledge
- Offer extended

(*Please note the process can slightly vary. The recruiter in charge will share more details when setting up the interview)

**Our commitment to celebrate diversity and generate belonging**

At the heart of our culture is a commitment to inclusion across race, gender, age, sexual orientation, religion, gender identity or expression, and accessibility. We strongly believe in an equal opportunity space, which is welcoming and celebrates the uniqueness of everyone who works here. We value different lived experiences and respect viewpoints, as we know unicity drives innovation. We want to make sure our people reflect the communities across the world we help travel.

**Eligibility criteria**:
**Please submit your resume in English**
**Please submit your resume in English