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 traveller's 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.
The job in brief:
Job Title -
Machine Learning Scientist
Working model - hybrid in Chiasso
Team - you will join the
Strategic Analytics team
within the Technology department.
Level - Professional
Location - Chiasso, Switzerland
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 Dynamic Pricing algorithms based on reinforcement 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 the field of machine learning.
Excellent knowledge of Supervised methods (Classification, Regression) and Unsupervised methods (Clustering, Feature Selection, Dimensionality Reduction)
Experience in Reinforcement Learning (Multi-Armed Bandit and Markov Decision Process)
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:
Able to find creative solutions to interesting problems
Curious with a constant desire to learn and collaborate
Previous experience with dynamic pricing algorithms
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 (36h as full time), with a half working day on Fridays
Flexible start and end of the working day, with core hours from 10:00 to 4:00 pm
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
1st Manager Interview + Technical Interview (1 hour)
2nd Manager Interview (1 hour)
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:
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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