PwC Acceleration Center India
Website:
pwc.com
Company:
https://www.linkedin.com/company/pwc-ac-india
Industries: Professional Services
Job details:
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 - Pharma Life Sciences- Manager, 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 Manager, you will lead teams and manage client accounts, focusing on strategic planning and mentoring junior staff. You are accountable for confirming project success and maintaining standards. Enhancing your leadership style, you motivate, develop, and inspire others to deliver quality. You are responsible for coaching, leveraging team members' unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same.
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.
Responsibilities
- Leading data science initiatives to transform raw data into actionable insights for informed decision-making
- Guiding teams in the design and development of robust data solutions using advanced analytics and statistical techniques
- Utilizing machine learning and artificial intelligence to drive data-driven decision-making and solve complex business problems
- Developing and implementing data pipelines and data models to support large-scale data analysis and visualization
- Overseeing the deployment of predictive modeling and natural language processing to enhance business growth
- Collaborating with stakeholders to identify opportunities for optimizing data utilization and improving performance
- Mentoring team members to develop their skills and encourage innovation in data science workflows
- Validating data quality and integrity within analytics frameworks to maintain compliance and security standards
- Encouraging the adoption of innovative technologies and leading practices across data and analytics teams
- Addressing conflicts and engaging in critical conversations with clients and team members to resolve issues effectively
What You Must Have
- At least a Bachelor's degree
- At least 8 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 experience with programming languages such as C++, R, and MATLAB
- Applying knowledge of neural networks and deep learning in practical scenarios
- Embracing change and innovation in AI-driven automation and cognitive solutions
- End to End Infra to deploy AI model (Pharma experience) - LLM Framework, LLM Ops - Rag pipeline
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