DATA SCIENTIST - Optimization Specialist
hace 12 días
Barcelona
Job description: NTT DATA is seeking a passionate Data Scientist with expertise in optimization algorithms to join our AI team. This is a fantastic opportunity to work alongside brilliant minds in data science, where you can learn and enrich yourself in a dynamic and innovative environment, leveraging cutting-edge Artificial Intelligence techniques to drive forward-thinking solutions in a company that's at the forefront of technological advancement. Qualifications: Bachelor's or master's degree in mathematics, Statistics, Informatics Engineering, Economics, or Physics. Courses in Artificial Intelligence, Analytics, Big Data, or similar fields are a plus. Experience: A minimum of 2 years of experience in projects implementing optimization algorithms, operations research or metaheuristics. Skills: • Required:, • Deep knowledge in classical and metaheuristic optimization algorithms such as Genetic Algorithms (GA), PSO, SA, etc., • Work with team members across multiple disciplines to understand the data, • Descriptive and exploratory statistics applied to detecting patterns and trends in data., • Advanced knowledge in Python., • English fluency, • Availability to travel, • Valuable:, • Experience using Git, • NLP, Generative AI, Deep Learning, methaeuristic algorithms, • Experience working with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services, including data storage, processing, and machine learning capabilities., • Big Data technologies: Spark, Big Query, Snowflake, Databricks, etc. Key Responsibilities: • Develop and implement classical and metaheuristic optimization algorithms such as Genetic Algorithms (GA), PSO, SA, etc. ., • Solve complex mathematical problems by designing and implementing custom optimization solutions., • Translate complex business rules into mathematical constraints for optimization problems., • Collaborate with stakeholders to understand requirements and design solutions tailored to specific operational challenges.