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Machine Learning Scientist

Chiasso, TI, Switzerland

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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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What you’ll bring

All qualifications

Core experience

  • Excellent knowledge of Supervised methods (Classification, Regression) and Unsupervised methods (Clustering, Feature Selection, Dimensionality Reduction)
  • Experience in Uncertainty Estimation (Monte Carlo Dropout, Deep Ensembles)
  • 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
Qualification wording
Excellent knowledge of Supervised methods (Classification, Regression) and Unsupervised methods (Clustering, Feature Selection, Dimensionality Reduction)
Experience in Uncertainty Estimation (Monte Carlo Dropout, Deep Ensembles)
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
Education & alternatives
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)

Tools in this posting

  • Python
  • SQL
  • Keras
  • Matplotlib
  • NumPy
  • pandas
  • Scipy
  • TensorFlow
  • MLflow
  • scikit-learn
  • PyTorch
Source — Tool mentions in context
- 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)
- HR interview (30 minutes) - 1st interview (Manager 1 hour): Machine learning + Python coding - 2nd interview (Director 45 min): Soft skills + machine learning knowledge
- Experience with Deep Learning (Recurrent Neural Networks, Convolutional Neural Networks, and Autoencoders) - Experience with Keras (and TensorFlow) or PyTorch Desirable:

Job description

View original posting ↗

Job Description

Job Title - Machine Learning Scientist
Working model - hybrid at Chiasso office
Team - You will join the Strategic Analytics team in 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 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:
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

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 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.

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

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Source & posting history

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Pay

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Location & working pattern

Chiasso, TI, Switzerland

Job Title - Machine Learning Scientist Working model - hybrid at Chiasso office Team - You will join the Strategic Analytics team in the Technology department.
Work authorization
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
Status in our records
Active
First seen by us
Sep 23, 2026
Recorded sightings
11
Last seen by us
Oct 9, 2026

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