Data Scientist- Sr Associate

In this role at PwC, you will be part of the data and analytics engineering team, where you will focus on utilizing advanced technologies to develop robust data solutions for clients. Your main responsibility will be transforming raw data into actionable insights, enabling informed decision-making, and driving business growth. Additionally, as part of the data science and machine learning engineering team, you will leverage advanced analytics and machine learning techniques to extract insights from large datasets, enabling data-driven decision-making. Your tasks will include developing predictive models, conducting statistical analysis, and creating data visualizations to solve complex business problems. As a member of the AI Engineering team at PwC, you will have the opportunity to design and deliver innovative AI applications that transform business operations. In your role as a Senior Associate, you will collaborate with cross-functional teams to develop scalable solutions, driving enterprise innovation and staying at the forefront of emerging technologies and industry trends. **Key Responsibilities:** - Design and implement innovative AI applications to improve business operations - Collaborate with cross-functional teams to develop scalable solutions - Stay abreast of emerging technologies and industry trends - Analyze business requirements to inform application development - Provide technical guidance and support to team members - Drive enterprise innovation through successful project execution - Confirm solutions meet quality standards and client expectations - Contribute to knowledge sharing and practices within the team **Qualifications Required:** - Bachelor's Degree - 3 years of experience in Data Science/ML/AI roles - Oral and written proficiency in English If you possess the following, it will set you apart: - Bachelor's Degree in Computer Science, Engineering - Hands-on experience with Generative AI solutions - Proficiency in Python and data science libraries - Familiarity with cloud platforms like Azure - Understanding of production-level AI systems - Experience with Docker and containerized deployments - Knowledge of NLP techniques and transformer architectures - Demonstrated track record of delivering AI-driven solutions - Experience in deploying AI models via APIs,