Digital and Cyber - Data and Cloud - Data Science and AI

Why PwC

At PwC, your growth is our priority. We fuel potential through coaching, feedback, and challenging work that helps you build a career path as unique as you are. You’re not just joining a team—you’re becoming part of a movement that’s shaping the future. Here, you can be yourself, work with purpose and boldness, and collaborate with talented people to deliver solutions that create real impact for clients and communities. Powered by inclusive teams, cutting-edge technology, and truly meaningful work, you’ll find endless opportunities to grow, lead, and go further.
Together, we set the future in motion.

Consulting LoS

At PwC Consulting, we lead with insight and deliver with purpose. You’ll work alongside experts across industries to design and deliver forward-looking solutions in areas such as strategy and enterprise transformation, operational excellence, digital innovation, cyber resilience, and risk management. Our reimagined operating model brings together sector-aligned, solution-led teams empowered to move fast, think boldly, and create real impact. Whether transforming finance, enabling digital change, or shaping national visions, you’ll be part of a collaborative, forward-thinking community—built to grow with you and the world around us.

BU Description 

The Digital & Cyber Business Unit brings together deep technology expertise and bold thinking to help organizations thrive in a connected, data-driven world. We support clients in reimagining how they operate, serve, and grow—by harnessing the power of digital products, emerging tech, cloud, data, and cyber resilience.

Whether shaping enterprise-wide transformation or enabling targeted innovation, we work at the intersection of strategy, technology, and trust—delivering scalable solutions that empower clients to move faster, think smarter, and lead with confidence.

Job Summary

Roles & Responsibilities

AI & Data Science Delivery 

• Develop, test, and deploy machine learning and statistical models for predictive analytics, forecasting, and optimization. 
• Design end-to-end AI workflows — from data collection and feature engineering to model training, validation, and deployment. 
• Conduct exploratory data analysis (EDA), uncovering insights that inform both strategic and operational decisions. 
• Implement scalable model pipelines using modern frameworks such as Databricks MLflow, Azure Machine Learning, or equivalent orchestration tools. 
• Collaborate with data engineers to ensure model readiness — defining data requirements, integrating with pipelines, and validating data quality. 
• Support clients in developing AI use cases, defining measurable KPIs, and ensuring business alignment. 
• Document and communicate analytical findings and model performance clearly to technical and non-technical audiences. 

Collaboration and Delivery Excellence 

• Work independently on assigned project components, managing deliverables and timelines effectively. 
• Contribute to proposal development and research activities supporting PwC’s Data & AI offerings. 
• Ensure all deliverables meet PwC’s quality standards, including reproducibility, auditability, and compliance with ethical AI practices. 
• Support client workshops and capability-building sessions on AI adoption, data literacy, and analytical best practices. 
• Collaborate with teams across the region, sharing insights and contributing to PwC’s Middle East AI knowledge base. 

Digital and Innovation 

• Actively explore and prototype emerging AI technologies, such as Generative AI, NLP, and Computer Vision, to identify new value opportunities. 
• Apply MLOps and automation techniques to improve scalability, monitoring, and lifecycle management of deployed models. 
• Participate in PwC’s innovation initiatives, contributing to the firm’s AI accelerators, reusable codebases, and solution frameworks. 

Skills and Competencies

Technical Skills 

• Proficiency in Python (Pandas, NumPy, Scikit-learn, PySpark, TensorFlow, PyTorch) for data analysis, ML, and AI development. 
• Strong experience with data wrangling, feature engineering, and model validation using structured and unstructured data. 
• Familiarity with SQL for analytical queries and Spark for distributed data processing. 
• Experience using Azure Machine Learning, Databricks, or similar cloud-based AI platforms for experimentation and deployment. 
• Knowledge of MLOps principles — CI/CD for ML, model versioning, and deployment automation. 
• Understanding of data science methodologies (CRISP-DM, OSEMN) and model evaluation techniques (cross-validation, bias/variance trade-offs). 
• Working knowledge of data visualization tools (Power BI, Matplotlib, Plotly) and experience creating analytical dashboards. 
• Awareness of AI governance and ethics frameworks, including responsible AI, model explainability, and fairness. 

Consulting & Delivery Skills 

• Ability to translate business problems into analytical frameworks and actionable insights. 
• Strong communication and storytelling skills; capable of presenting analytical findings to executive and operational audiences. 
• Collaborative and structured approach to problem-solving, balancing technical depth with business relevance. 
• Demonstrated ability to manage small workstreams, support proposal writing, and contribute to project delivery. 
• Bilingual Communication: Demonstrated fluency in both English and Arabic, with the ability to articulate complex concepts clearly to diverse stakeholders. 

Educational Qualifications & Certifications

• Bachelor’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, or Engineering. 
• Professional certifications such as Microsoft Certified: Azure AI Engineer Associate or Databricks Machine Learning Professional are advantageous. 
• 2 to 5 years of professional experience in data science, applied AI, or advanced analytics, preferably in a consulting or client-facing environment. 
• Hands-on experience delivering machine learning models to production using cloud or hybrid environments. 
• Exposure to data engineering concepts, enabling collaboration with platform and integration teams. 
• Regional or Middle East project experience is advantageous.