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PricewaterhouseCoopers (PwC)

Global professional services: assurance, tax, consulting

AI Engineer / Data Scientist

Applied Machine LearningPosted on Nov 13
Full-time

About the Job

Requirements

  • At least a bachelor's degree.
  • At least 8 years of experience.

Responsibilities

  • Translate business goals into AI and data engineering solutions for client engagements.
  • Lead the design and deployment of machine learning models, data pipelines, and scalable AI platforms.
  • Set portfolio-wide evaluation strategy and quality standards for AI-system behavior, performance, robustness, bias, explainability, and failure modes.
  • Establish review standards for technical controls and evidence, confirming that findings, limitations, and recommendations are clear and defensible.
  • Sponsor reusable evaluation tools, automated testing, reference datasets, monitoring capabilities, and evidence workflows across engagements.
  • Guide data wrangling, feature development, model training, and performance tuning across multiple use cases.
  • Evaluate data quality, model outputs, and platform integration points to support reliable solution delivery.
  • Advise clients on AI strategy, use case prioritization, and technology choices aligned to business needs.
  • Develop new ideas and technical approaches that advance AI capability across teams and engagements.
  • Coach practitioners on AI implementation methods, analytical problem solving, and modern development practices.
  • Identify opportunities to expand AI offerings and strengthen client relationships through credible delivery.
  • Adhere to firm technical standards, independence requirements, and professional conduct expectations.

Desired Qualifications

  • Preferred fields of study include Analytics/Data Science, Artificial Intelligence/Robotics, Computer Science/Information Systems, or Engineering.
  • Demonstrate director-level AI and data strategy across client engagements.
  • Establish rigorous AI evaluation standards covering failure modes, bias, drift, hallucinations, explainability, and guardrails.
  • Set enterprise architecture trade-offs and portfolio-level methods to measure and communicate technical and business outcomes.
  • Lead business growth through emerging technology solution development.
  • Develop thought leadership and executive-level client relationships.
  • Translate complex data concepts into business-focused recommendations.
  • Navigate ambiguity while guiding multidisciplinary delivery teams.

About the Company

PricewaterhouseCoopers (PwC)

Global professional services: assurance, tax, consulting

PwC provides assurance (audit), tax, legal services, consulting and deals advisory to organisations worldwide. It uses multidisciplinary teams across accounting, advisory, technology and industry, delivered through a global network of locally established firms that collaborate with technology partners to offer AI, cloud, managed services and digital trust. PwC differentiates itself with an integrated, global-local service model and technology-enabled offerings that address complex client needs across risk, transformation, reporting and sustainability. Its goal is to help clients improve governance, efficiency and value by supporting reporting accuracy, business transformation, risk management and sustainable practices.

Company size
10,001+
Company stage
Early VC
Total funding
$3.3M
Headquarters
London, United Kingdom
Founded
1989

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