IN_Senior Associate_ Data Science + Gen AI_ Data & Analytics_ Advisory_ Ban at pwc

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

29 Jun, 26

Salary

0.0

Posted On

31 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, PyTorch, TensorFlow, Transformers, Hugging Face, LLM APIs, Vector Databases, FAISS, Pinecone, RAG Frameworks, LangChain, LlamaIndex, Prompt Engineering, Model Fine-Tuning, RLHF, Embeddings

Industry

Professional Services

Description

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate Job Description & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes. Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decision-making and automation. *Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us . At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. " Job Description & Summary: A career within…. A career within Data and Analytics services will provide you with the opportunity to help organizations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organizational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organizations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. Responsibilities Design and implement Gen AI applications using LLMs (e.g., GPT, Claude, Llama) and multimodal models. Develop prompt engineering strategies, fine-tune models, and optimize outputs for accuracy and relevance. Build and deploy AI pipelines for text, image, audio, and video generation. Integrate AI models into existing systems using APIs (OpenAI, Anthropic, Hugging Face, etc.). Collaborate with product, design, and engineering teams to translate business needs into AI-driven features. Conduct experiments, perform model evaluation, and improve performance using RLHF, embeddings, and retrieval-augmented generation (RAG). Stay updated on emerging trends in AI research, model architectures, and generative technologies. Ensure compliance with ethical AI practices, data privacy, and model governance policies. Mandatory skill sets: Strong hands-on experience with Python, PyTorch, TensorFlow, or Transformers (Hugging Face). Familiarity with LLM APIs, vector databases (e.g., FAISS, Pinecone), and RAG frameworks (e.g., LangChain, LlamaIndex). Preferred skill sets: Experience building chatbots, copilots, or AI assistants. Contributions to open-source AI projects or published research in AI/ML. Years of experience required: 4-8 Education Qualification B.Tech / M.Tech / MBA / MCA Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: MBA (Master of Business Administration), Bachelor of Engineering Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills Python (Programming Language), PyTorch Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, AI Implementation, Analytical Thinking, C++ Programming Language, Communication, Complex Data Analysis, Creativity, Data Analysis, Data Infrastructure, Data Integration, Data Modeling, Data Pipeline, Data Quality, Deep Learning, Embracing Change, Emotional Regulation, Empathy, GPU Programming, Inclusion, Intellectual Curiosity, Java (Programming Language), Learning Agility, Machine Learning {+ 25 more} Desired Languages (If blank, desired languages not specified) Travel Requirements Available for Work Visa Sponsorship? Government Clearance Required? Job Posting End Date April 14, 2026 Are you ready to make a difference? Want to unlock new value by applying your unique perspective and talents? You can grow exponentially at PwC. Here, you can uncover hidden talents, build lifelong relationships rooted in trust and empathy and turn challenges into opportunities for innovation. We’ll help you grow your skills through challenging, meaningful work so you can go further.

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Responsibilities

Responsibilities include designing and implementing Generative AI applications using Large Language Models (LLMs) and multimodal models, developing prompt engineering strategies, and building/deploying AI pipelines for various data types. The role also requires integrating AI models via APIs, collaborating with cross-functional teams, and conducting model evaluation experiments.