Description We are seeking a talented and eager-to-learn Entry-Level Applied Scientist to join our team and contribute to the development of cutting-edge machine learning solutions for our customers in the MENA region. As an Entry-Level Applied Scientist, you will have the opportunity to apply off-the-shelf algorithms to well-defined problems, expand your science skills, and make meaningful contributions to the team. Key job responsibilities • Develop machine learning models, run A/B experiments, and perform statistical analysis to provide insights that drive business objectives. • Collaborate with cross-functional teams, including product managers, engineers, and more experienced applied scientists, to identify high-impact areas for innovation. • Proactively seek to identify business opportunities and insights and provide solutions to automate and optimize key business processes and policies based on a broad and deep knowledge of Amazon data, industry best-practices, and work done by other teams. • Establish scalable, efficient, and automated processes for large-scale data analysis, model development, validation, and deployment. • Analyze and extract relevant insights from large datasets using a variety of techniques, including machine learning, data mining, and statistical analysis. A day in the life Applying relevant science solutions for well defined problem statements. Collaborating with other scientists in the team and enhancing the solutions. About the team The MENA Science team works closely with the business and engineering teams in building ML solutions that create an impact for MENA businesses. This is a great opportunity to leverage your machine learning and data mining skills to create a direct impact on consumers and end users. Basic Qualifications - Master's degree in a quantitative field such as computer science, mathematics, statistics, machine learning, or an equivalent quantitative field, or Bachelor's degree and 2+ years of relevant experience. - Experience with coding in Python or any relevant scripting language. - Apply off-the-shelf algorithms to well-defined problems, and eager to learn new techniques. Preferred Qualifications - Experience in applying machine learning solutions to real world problem statements. - Basic understanding of any one of the following- large language models, NLP (Information retrieval, Machine Translation), Computer Vision, Classification models using Boosting/Bagging or Deep Neural Networks.