Data Scientist- Associate 2

Role Overview: At PwC, you will be part of the data and analytics engineering team, focusing on leveraging advanced technologies to design and develop robust data solutions for clients. Your role will involve transforming raw data into actionable insights to drive business growth. In the field of data science and machine learning engineering, you will utilize advanced analytics and machine learning techniques to extract insights from large datasets and enable data-driven decision-making. Your responsibilities will include developing predictive models, conducting statistical analysis, and creating data visualizations to solve complex business problems. Key Responsibilities: - Design and implement scalable AI applications - Conduct applied research in Generative AI and advanced learning - Collaborate with team members to enhance project outcomes - Develop technical skills to support project tasks - Build and maintain relationships with clients - Analyze data to derive insights and inform decisions - Adapt to evolving technologies and methodologies - Contribute to a significant team focused on innovation Qualifications Required: - Master's Degree in Computer Science, Engineering, Econometrics, Statistics, Business Analytics, or Informatics - 2 years of experience - Oral and written proficiency in English required Additional Details: Joining PwC Acceleration Centers (ACs) will provide you with the opportunity to actively support various services, from Advisory to Assurance, Tax, and Business Services. You will engage in challenging projects, receive dynamic and digitally enabled training, and work with advanced technologies in a team dedicated to driving enterprise innovation. What Sets You Apart: - Bachelor's Degree in Computer Science or Engineering preferred - Proficiency in Python and data science libraries - Experience with Generative AI and prompt engineering - Knowledge of NLP techniques and transformer architectures - Familiarity with cloud platforms, preferably Azure - Understanding of production-level AI systems - Experience with Docker and containerized deployments - Desire to innovate and automate processes - A mindset of continuous learning and technical curiosity,