Machine Learning Scientist

Summary

Join lastminute.com, a European Travel-Tech leader, as a Machine Learning Scientist working fully remotely from Spain. You will develop real-time machine learning solutions and dynamic pricing algorithms using reinforcement learning. Collaboration with a cross-functional team is key. This permanent, full-time (36 hours/week) position requires a Ph.D. or Master's degree with relevant experience and expertise in machine learning techniques. The company offers a shorter working week, flexible hours, and various professional development opportunities. Additional perks include travel discounts and support for life's significant moments.

Requirements

• 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

Responsibilities

• 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

Preferred Qualifications

• Able to find creative solutions to interesting problems
• Curious with a constant desire to learn and collaborate
• Previous experience with dynamic pricing algorithms

Benefits

• 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
• 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
• 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