Assurance-Risk Modeling Services-AI Data Scientist-Manager

Overview

At PwC, our people in risk and compliance focus on maintaining regulatory compliance and managing risks for clients, providing advice, and solutions. They help organisations navigate complex regulatory landscapes and enhance their internal controls to mitigate risks effectively. In actuarial services at PwC, you will be responsible for analysing and managing financial risks for clients through statistical modelling and data analysis. Your work will generate valuable insights and recommendations to help businesses make informed decisions and mitigate potential risks.

Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member’s unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same.

Skills

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

• Analyse and identify the linkages and interactions between the component parts of an entire system.
• Take ownership of projects, ensuring their successful planning, budgeting, execution, and completion.
• Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables.
• Develop skills outside your comfort zone, and encourage others to do the same.
• Effectively mentor others.
• Use the review of work as an opportunity to deepen the expertise of team members.
• Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate.
• Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.
  
  

• Contribute to the development and deployment of GenAI solutions including prompt engineering, retrieval-augmented generation (RAG), fine-tuning, AI agents, and multi-agent systems (MAS), with solutions operationalized through Palantir Foundry workflows, applications, and ontology-backed data products.
• Develop and integrate econometric and statistical models such as generalized linear models (GLMs), time-series models, and semi-parametric approaches into Foundry-based pipelines and analytical workflows.
• Build, train, and deploy machine learning models including XGBoost, random forests, and support vector machines, leveraging Foundry’s distributed compute environment (Spark / PySpark) for scalable feature engineering and model execution.
• Design, build, and maintain production-grade data pipelines in Palantir Foundry, including transforms on structured and unstructured datasets, supporting end-to-end ingestion, transformation, feature generation, and model scoring.
• Leverage Python, PySpark, SQL, and related Foundry tooling for large-scale data processing, transformation, and integration across multiple internal and external data sources.
• Contribute to Foundry ontology design and implementation, supporting ontology objects and links with pipelines aligned to modeling, application, and client workflow requirements.
• Ensure data quality, lineage, governance, and security across Foundry datasets and pipelines, supporting auditability and regulatory review.
• Support compliance with model risk management and AI governance standards including SR 11-7, Colorado SB21-169, NIST frameworks, ISO 42001, and NAIC Model Bulletins throughout model development, validation, deployment, and monitoring.
• Apply DevOps and MLOps best practices including Git-based version control, CI/CD, automated testing, infrastructure-as-code, and system monitoring in collaboration with Foundry, cloud, and data engineering teams.
• Deploy AI and analytics solutions into real-world client environments, integrating models with Foundry-powered applications, dashboards, and decision workflows.
• Monitor and research emerging AI, GenAI, and data-platform capabilities, incorporating new Foundry features and best practices into solution design.
• Support project delivery and client engagements, working with structured and unstructured data in Foundry to improve business processes, operational workflows, and data-driven decision-making.
• Support documentation and technical analysis for validators, auditors, and regulators, including detailed descriptions of Foundry pipelines, ontologies, modeling logic, and controls; communicate complex concepts clearly to non-technical stakeholders.
• Collaborate with cross-functional teams including data engineers, architects, and data scientists to deliver scalable, high-quality Foundry-enabled AI and analytics solutions aligned to client needs.
• Mentor and support associates and senior associates, providing coaching, technical guidance, and hands-on support across AI modeling and Palantir Foundry development.
• Support business development activities, including technical solutioning, participation in sales cycles, and contribution to proposals that highlight Palantir-enabled AI and analytics capabilities.
• Contribute to the development of internal GenAI assets and foundational platforms, building reusable Foundry pipelines, ontologies, and analytics components to scale the firm’s practice.
  
  

A degree in statistics, mathematics, electrical engineering, physics, econometrics, computer science, or another related technical field.

Credentials - Good to have: A master's degree or PhD in a related field from a premium institute is preferred but is not required. Min years of Experience Requirement (Credential) - 6 years