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.