Assurance-Risk Modeling Services-AI Data Scientist-Senior Associate

Job description

Industry/Sector Not Applicable Specialism Assurance Management Level Senior Associate Job Description & Summary 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. Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow. Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Respond effectively to the diverse perspectives, needs, and feelings of others. Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems. Use critical thinking to break down complex concepts. Understand the broader objectives of your project or role and how your work fits into the overall strategy. Develop a deeper understanding of the business context and how it is changing. Use reflection to develop self awareness, enhance strengths and address development areas. Interpret data to inform insights and recommendations. 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 operationalization of GenAI solutions including prompt engineering, retrieval-augmented generation (RAG), fine-tuning, AI agents, and multi-agent systems (MAS), with solutions deployed through Palantir Foundry applications, workflows, 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 analytical pipelines and decision workflows. · Build, train, and deploy machine learning models including XGBoost, random forests, and support vector machines, leveraging Foundry’s Spark / PySpark environment for scalable feature engineering, training, and inference. · Design, build, and maintain production-grade data pipelines in Palantir Foundry, including transforms on structured and unstructured data, supporting ingestion, transformation, feature generation, model scoring, and downstream analytics. · Leverage Python, PySpark, SQL, and Foundry tooling for large-scale data processing, integration, and automation across diverse internal and external data sources. · Support Foundry ontology design and implementation, contributing data engineering and modeling context and building pipelines that back ontology objects and links aligned to FMRE business and application requirements. · Ensure data quality, lineage, governance, and security across Foundry datasets and pipelines, enabling auditability, traceability, 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 pipelines, automated testing, infrastructure-as-code, and system monitoring in collaboration with Foundry, cloud, and data engineering teams. · Design, deploy, and support AI and analytics solutions in real-world client environments, integrating models with Foundry-powered applications, dashboards, and operational workflows. · Monitor and research emerging AI, GenAI, and data-platform trends, incorporating new Palantir Foundry capabilities and best practices into solution design. · Support project delivery and client engagements, using Foundry to process large-scale structured and unstructured data 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, and 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. · Support business development activities, including technical solutioning, participation in sales cycles, and contribution to proposals highlighting Palantir-enabled AI, analytics, and decision-intelligence capabilities. · Contribute to the development of internal GenAI assets and foundational platforms, building reusable Palantir Foundry pipelines, ontologies, and analytics components to scale the firm’s practice. Minimum Educational Qualifications: A degree in statistics, mathematics, electrical engineering, physics, econometrics, computer science, or another related technical field. 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 – 4-7 years Travel Requirements Job Posting End Date