Data Scientist

Há 1 mês


Lisboa, Lisboa, Portugal Capgemini Tempo inteiro
About the Role

We are seeking a highly skilled Data Scientist to join our team in Lisbon. As a Data Scientist, you will be responsible for leading and contributing to end-to-end data science projects, including problem formulation, data collection, analysis, model development, and deployment.

Key Responsibilities
  • Develop advanced machine learning models to address complex business problems, utilizing techniques such as deep learning, natural language processing, and ensemble methods.
  • Work closely with cross-functional teams to understand business requirements, identify opportunities for data-driven solutions, and communicate findings effectively.
  • Drive innovation by researching and implementing state-of-the-art algorithms and techniques to improve predictive performance and model interpretability.
  • Collaborate with data engineers to optimize data pipelines and ensure scalability, reliability, and efficiency of data processing workflows.
Requirements
  • Master's degree or Ph.D. in Computer Science, Statistics, Mathematics, or a related field.
  • Proven experience as a Data Scientist (at least 3 years), machine learning, or predictive analytics roles.
  • Proficiency in programming languages such as Python or R and experience with data manipulation and analysis libraries (e.g., Pandas, NumPy).
  • Strong understanding of machine learning concepts, algorithms, and techniques with proven experience in building and deploying production-quality models.
  • Demonstrated experience in working with large-scale datasets and distributed computing frameworks (e.g., Spark).
About Capgemini

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. We promote equality and dignity in all aspects of recruitment and employment, as well as employment offers and promotions made according to competence and ability or performance, respectively.



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