PricewaterhouseCoopers

Line of Service

Advisory

Industry/Sector

GPS X-Sector

Specialism

Operations

Management Level

Manager

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.

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.

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: At PwC, our purpose is to build trust in society and solve important problems. We’re a network of firms in 157 countries with more than 300,000 people who are committed to delivering quality in Assurance, Advisory and Tax services. Within Advisory, PwC has a large team that focus on transformation in Government through Digital inclusion. The open position is for a candidate who desires to work with government clients and bring about a change in society. A successful candidate will be expected to work pro-actively and effectively on multiple client engagements over the period of time and take ownership of the entire project delivery he/she entrusted with.

Responsibilities:

1. Lead the design, development and deployment of advanced AI/ML models, particularly in the domains of NLP and Generative AI

2. Architect and implement end-to-end solutions leveraging large language models (LLMs), transformers and deep learning architectures

3. Develop customized NLP pipelines for tasks such as text classification, summarization, entity recognition, semantic search and conversational AI

4. Drive innovation in generative AI use cases such as prompt engineering, text generation, RAG, multimodal AI and fine-tuning LLMs

5. Collaborate with product managers, data engineers and domain experts to translate business requirements into intelligent solutions

6. Mentor AI/ML teams and provide technical leadership on best practices, frameworks and emerging technologies

7. Ensure responsible AI practices including bias mitigation, model explainability and governance

8. Publish technical papers, contribute to open-source projects and represent the organization in AI forums and communities

9. Evaluate and integrate new AI tools, APIs and models into production-grade systems

Mandatory skill sets:

• 8+ years of experience in AI/ML, with deep expertise in NLP, Generative AI and applied Data Science · Hands-on experience with LLMs (e.g., GPT, BERT, LLaMA, T5), transformer architectures and prompt engineering · Strong coding and modeling experience using Python and ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers) · Experience with NLP tasks like question answering, summarization, text generation, sentiment analysis, topic modeling · Proven ability to fine-tune and deploy LLMs on domain-specific tasks and datasets · Familiarity with vector databases (e.g., FAISS, Pinecone), embeddings and retrieval-augmented generation (RAG)
• Strong foundation in statistics, probability and machine learning algorithms · Proficiency with ML lifecycle tools (e.g., MLflow, DVC), containerization (Docker) and model deployment on cloud platforms (AWS, GCP, Azure) · Excellent communication and leadership skills to influence stakeholders and guide teams

Preferred skill sets:

• Experience with reinforcement learning (RLHF), diffusion models or multimodal learning · Knowledge of MLOps tools and workflow orchestration (e.g., Airflow, Kubeflow) · Familiarity with ethical AI practices, model interpretability (e.g., SHAP, LIME) and AI compliance frameworks · Experience with speech-to-text, OCR or cross-lingual NLP · Contributions to research papers, patents or open-source AI/ML libraries · Certification in AI/ML from recognized platforms or institutions (e.g., Stanford, Coursera, AWS, GCP)

Years of experience required:

8+ years

Education qualification:

Master’s or bachelor's degree in computer science, Artificial Intelligence, Data Science, Mathematics, Statistics or a related technical field. A Ph.D. is a plus.

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required: Master Degree, Bachelor Degree

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

AI Programming, Standard ML (Programming Language)

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Coaching and Feedback, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling {+ 32 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Available for Work Visa Sponsorship?

Government Clearance Required?

Job Posting End Date

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