Machine Learning Engineer II - Promotions Optimization

About Us: At Booking.com, data drives our decisions. Technology is at our core. And innovation is everywhere. But our company is more than datasets, lines of code or A/B tests. We’re the thrill of the first night in a new place. The excitement of the next morning. The friends you encounter. The journeys you take. The sights you see. And the memories you make. Through our products, partners and people, we make it easier for everyone to experience the world. Leadership/Team Quote: The opening is for the Promotions Optimization team in the Central Tech department. The team is responsible for building and enabling ML decisioning for discounts and promotions across the site, and taking a key role in the customer journey. You’ll work with top notch engineers and machine learning scientists on bringing it to the next level and enabling optimal user experience while having a significant impact on the business. The work will focus on data and ML foundations for reusable training, optimization and deploying causal machine learning models. Role Description: You’ll work with top notch engineers and machine learning scientists on bringing it to the next level and enabling optimal user experience while having a significant impact on the business. The work will focus on data and ML foundations for reusable training, optimization and deploying causal machine learning models. Key Job Responsibilities and Duties: Data pre-processing and analysis: Collaborate with data scientists and data engineers to collect, clean, pre-process, and transform large and wide datasets for model features and data monitoring. Conduct exploratory data analysis (EDA) to uncover insights and identify patterns that boost the model performance. Model evaluation and optimization: Conduct detailed model evaluation metrics and validation to ensure accuracy, reliability, and scalability. Optimize model performance by fine-tuning hyper parameters, feature engineering, and applying techniques such as ensemble learning and continuous learning. Building machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide personalized recommendations to users. Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies. Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members. Qualifications & Skills: Bachelor’s or master’s degree in computer science, Engineering, Statistics, or a related field. Minimum of 5 years of experience as a Machine Learning Engineer or a similar role, with a consistent record of successfully delivering ML solutions. Strong programming skills in Python (Additional knowledge in Java, Perl and Scala are an advantage) . Experience with cloud frameworks like AWS sagemaker and training models such as using TensorFlow, PyTorch, lightgbm or scikit-learn. Experience with data at scale using MySQL, Pyspark, Airflow, Snowflake and similar frameworks. Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, matplotlib and BI tools. Proficient knowledge of machine learning algorithms, statistical models, optimization and data structures. Experience with experimental design, causal inference, A/B testing, and evaluation metrics for ML models. Experience of working on products that impact a large customer base is an advantage Excellent communication in English; written and spoken Benefits & Perks - Global Impact, Personal Relevance: Booking.com’s Total Rewards Philosophy is not only about compensation but also about benefits. We offer a competitive compensation and benefits package, as well unique-to-Booking.com benefits which include: Annual paid time off and generous paid leave scheme including: parent, grandparent, bereavement, and care leave Hybrid working including flexible working arrangements, and up to 20 days per year working from abroad (home country) Industry leading product discounts - up to 1400 per year - for yourself, including automatic Genius Level 3 status and Booking.com wallet credit Diversity, Equity and Inclusion (DEI) at Booking.com: Diversity, Equity & Inclusion have been a core part of our company culture since day one. This ongoing journey starts with our very own employees, who represent over 140 nationalities and a wide range of ethnic and social backgrounds, genders and sexual orientations. Take it from our Chief People Officer, Paulo Pisano: “At Booking.com, the diversity of our people doesn’t just build an outstanding workplace, it also creates a better and more inclusive travel experience for everyone. Inclusion is at the heart of everything we do. It’s a place where you can make your mark and have a real impact in travel and tech.” We ensure that colleagues with disabilities are provided the adjustments and tools they need to participate in the job application and interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Application Process: Let’s go places together: How we Hire This role does not come with relocation assistance. Booking.com is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We strive to move well beyond traditional equal opportunity and work to create an environment that allows everyone to thrive. Pre-Employment Screening If your application is successful, your personal data may be used for a pre-employment screening check by a third party as permitted by applicable law. Depending on the vacancy and applicable law, a pre-employment screening may include employment history, education and other information (such as media information) that may be necessary for determining your qualifications and suitability for the position.