Machine Learning Scientist

• Full-time
• Department: Technology

Company Description

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.

Job Description

Job Title - Machine Learning Scientist

Working model - hybrid from Switzerland

Team - you will join the Strategic Analytics team within the Technology department.

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

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
• 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:

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.

Please submit your resume in English

Please submit your resume in English