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
Booking.com’s Total Rewards Philosophy is not only about compensation but also about benefits. We offer a competitive , 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
Application Process:
Let’s go places together:
This role does not come with relocation assistance.
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.
