**Industry/Sector** Not Applicable **Specialism** Data, Analytics & AI **Management Level** Senior Associate **Job Description & Summary** The Opportunity Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day. As an LLM - Engineer - Senior Associate, you will play a pivotal role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Data and Analytics Engineering practice, you will focus on leveraging advanced analytics and statistical techniques to extract insights from large datasets and drive data-driven decision-making. As a Senior Associate, you will build meaningful client connections and learn how to manage and inspire others. You will navigate increasingly complex situations, growing your personal brand and deepening your technical skills. In this role at PwC Acceleration Center India, you will work on exploratory and descriptive analysis, statistical modeling, and creating data visualizations to help solve complex business problems and inform strategic decisions. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you will be comfortable when the path forward isn’t clear, asking questions, and using these moments as opportunities to grow. This position offers a unique opportunity to develop a deeper understanding of the business context and how it is changing, while upholding professional and technical standards. Responsibilities - Designing and developing data solutions to transform raw data into actionable insights - Leveraging advanced analytics and statistical techniques to extract insights from large datasets - Conducting exploratory and descriptive analysis to solve complex business problems - Creating data visualizations to inform strategic decisions and drive business growth - Utilizing machine learning and artificial intelligence to enhance data-driven decision making - Building and managing data pipelines and data lakes for efficient data processing - Implementing data science algorithms and workflows to optimize data analysis - Collaborating with clients to understand their data needs and deliver tailored solutions - Applying programming languages such as C++, R, and MATLAB for data modeling and analysis - Employing tools like TensorFlow and Scikit-Learn for predictive modeling and deep learning - Confirming data quality and integrity throughout the data engineering process - Mentoring junior team members in data science methodologies and best practices What You Must Have - At least a Bachelor's degree - At least 4 years of experience - Oral and written proficiency in English required What Sets You Apart - Preference for at least one of the following fields of study: Artificial Intelligence and Robotics, Business Analytics, Computer and Information Science, Computer Engineering, Computer Programming, Data Processing/Analytics/Science, Engineering, Information Technology, Machine Learning, Management Information Systems, Mathematics, Statistics, Systems Engineering - Demonstrating proficiency in data science algorithms and workflows - Utilizing machine learning and deep learning techniques effectively - Excelling in complex data analysis and predictive modeling - Leveraging programming languages such as Python, R, and MATLAB - Applying natural language processing and neural network methodologies - Managing data pipelines and confirming data quality in analytics projects - End to End Infra to deploy AI model (Healthcare experience) - LLM Framework, LLM Ops - Rag pipeline **Travel Requirements** Not Specified **Job Posting End Date**