PwC - Data Science Manager

Responsibilities:

- Leading the design and development of advanced data solutions to transform raw data into actionable insights.

- Driving data-driven decision-making through exploratory and descriptive analysis and statistical modeling.

- Utilizing advanced analytics and statistical techniques to extract insights from large datasets.

- Developing and implementing data visualizations to solve complex business problems and inform strategic decisions.

- Managing and coaching teams to apply sound judgment and solve through complexity.

- Applying systems thinking to identify underlying problems and opportunities within data projects.

- Validating outcomes with clients and acting on feedback to enhance project success.

- Directing teams through ambiguous and challenging situations while maintaining composure.

- Promoting the use of innovative technologies and leading practices in data science and analytics.

- Building and maintaining relationships with stakeholders to identify and address data challenges.

- Overseeing the deployment of scalable data engineering solutions to support business growth.

What You Must Have:

- At least 12 years of experience.

- Oral and written proficiency in English required.

- Experience with enterprise cloud AI platforms - Azure AI Foundry integrated with Microsoft Fabric and Purview, Amazon Bedrock with Knowledge Bases and Guardrails, or Google Vertex AI with BigQuery and Agentspace for building, governing, and deploying production-grade Gen AI and Agentic AI solutions at scale.

- Awareness of AI governance platforms and observability tools (LangSmith, Arize, etc.) for monitoring, tracing, and debugging production AI systems.

- Capable of LLM selection decisions (GPT, Claude, Gemini, Llama, Mistral, etc.) against enterprise requirements including cost, latency, and compliance.

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 advanced skills in data science algorithms and workflows.

- Utilizing machine learning and deep learning techniques for innovative solutions.

- Leading complex data engineering projects with a focus on operational excellence.

- Applying systems thinking to identify and solve underlying problems.

- Excelling in strategic questioning and data-driven decision making.

- Validating outcomes with clients and acting on feedback to drive results.