Machine Learning Scientist
hace 3 semanas
At lastminute.com, we live for the holidays. We are the European Travel-Tech leader in Dynamic Holiday Packages. With technology, we turn spontaneous thoughts into meaningful experiences, helping people travel the world.
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 holidaymakers. 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 DescriptionJob 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
- 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
- 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
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.
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
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:By submitting your information and application, you confirm that you are legally authorised to work in the country of employment and that you do not require visa sponsorship to obtain employment visa status.
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