Data Scientist Senior - Genai Solutions
The ideal candidate as Senior Data Scientist in NTT DATA will have a mix of skills including Generative AI hands-on capability (preferably on Azure/GCP and on-premise) engineering best practices, statistical expertise, Machine and Deep Learning skills and a strong business sense.
Your contribution in this role: Collaborate with data scientists, data engineers, ML Engineers, product managers, business analysts,
and stakeholders from internal teams and external clients Manage multiple projects simultaneously Lead and coordinate the Data Scientists involved in the projects Act as the main point of contact with client-side stakeholders Ensure that project tasks are delivered on time and executed to a high standard The ideal profile Experience of at least 3-5 years as data scientist; Strong Python (mandatory) and SQL coding; Knowledge of Java/Scala or C++/R is a plus; Tensorflow and Pytorch knowledge with a focus over Computer Vision solutions; Knowledge of ML solutions architecture and Generative AI pipelines; Cloud and hybrid ML implementations; Incorporate new, cutting edge business intelligence, machine learning, and alternative data practices into wider organization to drive efficiencies and generate revenue; Own the full stack execution of data science projects from data wrangling, model development, presentation, measuremen
Your contribution in this role: Collaborate with data scientists, data engineers, ML Engineers, product managers, business analysts,
and stakeholders from internal teams and external clients Manage multiple projects simultaneously Lead and coordinate the Data Scientists involved in the projects Act as the main point of contact with client-side stakeholders Ensure that project tasks are delivered on time and executed to a high standard The ideal profile Experience of at least 3-5 years as data scientist; Strong Python (mandatory) and SQL coding; Knowledge of Java/Scala or C++/R is a plus; Tensorflow and Pytorch knowledge with a focus over Computer Vision solutions; Knowledge of ML solutions architecture and Generative AI pipelines; Cloud and hybrid ML implementations; Incorporate new, cutting edge business intelligence, machine learning, and alternative data practices into wider organization to drive efficiencies and generate revenue; Own the full stack execution of data science projects from data wrangling, model development, presentation, measuremen