LLM Engineer - Senior Associate

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 a LLM - Engineer - Senior Associate, you will leverage advanced analytics and statistical techniques to transform raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Data and Analytics Engineering practice, you will focus on exploratory and descriptive analysis, statistical modeling, and creating data visualizations to solve complex business problems and inform strategic decisions.

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. You are expected to anticipate the needs of your teams and clients, delivering quality solutions. Embracing increased ambiguity, you will be comfortable when the path forward isn’t clear, using these moments as opportunities to grow.

In this role at PwC Acceleration Center India, you will respond effectively to diverse perspectives and use a broad range of tools and methodologies to generate new ideas and solve problems. You will interpret data to inform insights and recommendations, upholding professional and technical standards while developing a deeper understanding of the business context and how it is evolving.

Responsibilities

- Leveraging advanced analytics and statistical techniques to extract insights from large datasets
- Designing and developing robust data solutions to transform raw data into actionable insights
- Conducting exploratory and descriptive analysis to inform strategic decision-making
- Creating data visualizations to solve complex business problems
- Utilizing machine learning algorithms and tools such as TensorFlow and Scikit-Learn to enhance data-driven decision-making
- Building and maintaining data pipelines and data lakes to support data engineering efforts
- Applying predictive modeling techniques to anticipate client needs and drive business growth
- Collaborating with cross-functional teams to implement AI-driven automation and cognitive solutions
- Upholding professional and technical standards in data science projects
- Mentoring junior team members in data science methodologies and techniques

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 advanced machine learning techniques for predictive modeling
- Excelling in complex data analysis and data-driven decision making
- 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

Utilize cloud platforms such as Azure, AWS, or GCP for model training, deployment, and scaling. 

- Exposure Generative AI or advanced AI frameworks (Langchain, Crew AI etc.)

Travel Requirements

Not Specified

Job Posting End Date