Vanguard
hackajob is collaborating with Vanguard to connect them with exceptional professionals for this role. Project Contractor Project Contractor Summary Contract role to design and deliver a proof-of-concept knowledge graph modeling investment fund data for one of the world's largest asset managers. You will encode business rules, regulatory constraints, and identifier relationships as machine-readable ontologies - directly eliminating manual fund data processes and enabling automated validation across thousands of funds in 6 global markets. Defined POC scope, executive sponsorship, and weekly technical guidance from two of the most recognized knowledge graph practitioners in financial services. What You'll Deliver (POC Scope) An investment fund ontology (OWL 2 / RDF / Linked Data) modeling the product hierarchy: Fund > ShareClass > Listing > Security, with 73+ identifier types (ISIN, SEDOL, CUSIP, LEI, Bloomberg, and more) governed across US, UK, Ireland, Australia, Canada, and Mexico SHACL validation shapes encoding business rules as executable constraints - e.g., "A US-domiciled ETF listing must have a valid ISIN" - that flag violations at fund launch and throughout the fund lifecycle SKOS concept schemes harmonizing vocabulary across 8+ internal systems, providing a semantic bridge between source-of-record platforms Data integration pipelines mapping relational data into RDF triples (Turtle/N-Quads) using R2RML, rdflib, or equivalent mapping tooling API layer enabling downstream applications to consume graph data programmatically Automated governance reports surfacing data quality gaps, missing identifiers, and cross-system inconsistencies Required Skills 5+ years hands-on experience building and deploying RDF/OWL ontologies in production (not solely academic - you have shipped something real) SHACL for constraint validation, data quality enforcement, and shape-based governance SPARQL 1.1 - fluent in complex queries, property paths, and federated queries At least one enterprise triple store / graph platform: TopBraid, GraphDB (Ontotext), Stardog, RDFox, Amazon Neptune (RDF mode), or equivalent Python or Java for data transformation, pipeline orchestration, and integration work Familiarity with financial or securities identifiers (ISIN, SEDOL, CUSIP, LEI, or similar instrument identification schemes) - you don't need to be a fund accountant, but you need to understand what an identifier is and why it matters Working knowledge of data governance - you understand why constraints exist, not just how to code them Preferred Experience Financial services domain: fund data, securities master, regulatory compliance (MiFID, UCITS, listing rules) FIBO (Financial Industry Business Ontology) or similar financial ontologies TopBraid EDG / GraphWise (our target platform - evaluation input from this hire is welcome) SKOS for vocabulary management and cross-system term harmonization R2RML / RML or equivalent relational-to-RDF mapping standards Ontology design patterns, modular schema design, ontology versioning (Git-based workflows) Enterprise-scale data modeling (thousands of entities, multi-market, multi-product-type) Exposure to rules engines, inference, or deterministic AI (SHACL-based reasoning, business rules automation) Agile delivery in a regulated environment How We Work Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.
hackajob is collaborating with Vanguard to connect them with exceptional professionals for this role. Project Contractor Project Contractor Summary Contract role to design and deliver a proof-of-concept knowledge graph modeling investment fund data for one of the world's largest asset managers. You will encode business rules, regulatory constraints, and identifier relationships as machine-readable ontologies - directly eliminating manual fund data processes and enabling automated validation across thousands of funds in 6 global markets. Defined POC scope, executive sponsorship, and weekly technical guidance from two of the most recognized knowledge graph practitioners in financial services. What You'll Deliver (POC Scope) An investment fund ontology (OWL 2 / RDF / Linked Data) modeling the product hierarchy: Fund > ShareClass > Listing > Security, with 73+ identifier types (ISIN, SEDOL, CUSIP, LEI, Bloomberg, and more) governed across US, UK, Ireland, Australia, Canada, and Mexico SHACL validation shapes encoding business rules as executable constraints - e.g., "A US-domiciled ETF listing must have a valid ISIN" - that flag violations at fund launch and throughout the fund lifecycle SKOS concept schemes harmonizing vocabulary across 8+ internal systems, providing a semantic bridge between source-of-record platforms Data integration pipelines mapping relational data into RDF triples (Turtle/N-Quads) using R2RML, rdflib, or equivalent mapping tooling API layer enabling downstream applications to consume graph data programmatically Automated governance reports surfacing data quality gaps, missing identifiers, and cross-system inconsistencies Required Skills 5+ years hands-on experience building and deploying RDF/OWL ontologies in production (not solely academic - you have shipped something real) SHACL for constraint validation, data quality enforcement, and shape-based governance SPARQL 1.1 - fluent in complex queries, property paths, and federated queries At least one enterprise triple store / graph platform: TopBraid, GraphDB (Ontotext), Stardog, RDFox, Amazon Neptune (RDF mode), or equivalent Python or Java for data transformation, pipeline orchestration, and integration work Familiarity with financial or securities identifiers (ISIN, SEDOL, CUSIP, LEI, or similar instrument identification schemes) - you don't need to be a fund accountant, but you need to understand what an identifier is and why it matters Working knowledge of data governance - you understand why constraints exist, not just how to code them Preferred Experience Financial services domain: fund data, securities master, regulatory compliance (MiFID, UCITS, listing rules) FIBO (Financial Industry Business Ontology) or similar financial ontologies TopBraid EDG / GraphWise (our target platform - evaluation input from this hire is welcome) SKOS for vocabulary management and cross-system term harmonization R2RML / RML or equivalent relational-to-RDF mapping standards Ontology design patterns, modular schema design, ontology versioning (Git-based workflows) Enterprise-scale data modeling (thousands of entities, multi-market, multi-product-type) Exposure to rules engines, inference, or deterministic AI (SHACL-based reasoning, business rules automation) Agile delivery in a regulated environment How We Work Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.
Vanguard
hackajob is collaborating with Vanguard to connect them with exceptional professionals for this role. Overview The Head of Validation, Model Risk is a senior leadership role responsible for setting enterprise direction for model validation-delivering independent, risk-based oversight across a diverse portfolio of models spanning investment and risk management, fraud and compliance, finance and HR, and rapidly evolving Gen AI and agentic use cases. This role serves as the senior authority for model validation, setting the bar for defensible methodologies, rigorous challenge, and clear, decision-ready risk communication to senior leaders. The Head of Validation will strengthen model risk culture and lifecycle discipline across the enterprise-driving timely issue remediation, elevating validation quality and consistency, and ensuring Vanguard's practices remain aligned with regulatory and audit expectations. Responsibilities Leadership & Team Management Leads a high performing, multidisciplinary model validation team responsible for validating a diverse portfolio of models including investment and risk management, fraud and compliance, finance and HR, as well as Gen AI and Agentic use cases Develop and mentor talent to promote strong technical capabilities and a high-quality validation process Validation Oversight & Approval Serve as the final approval authority for validation reports on higher-risk models Ensure validation conclusions are robust, well supported, and communicated clearly to stakeholders with varying levels of technical expertise Model Risk Governance & Lifecycle Management Oversee adherence to enterprise model lifecycle requirements-including model inventory accuracy, change management, ongoing monitoring, and issue remediation. Drive timely resolution of model related issues and non compliance, escalating when necessary Strengthen model risk culture across the enterprise through targeted training, outreach, and proactive engagement with model owners and developers Methodology & Practice Leadership Define, maintain, and continually enhance the methodologies and test approaches used in model validation Ensure comprehensive assessment of conceptual soundness, performance, data quality, implementation accuracy, and other model risk considerations Lead the evolution of validation techniques for emerging modeling approaches, including LLM enabled and agentic systems Standards, Policies & Quality Assurance Own the enterprise's model development and model validation standards, guidelines, procedures, and templates. Establish and oversee quality assurance mechanisms-including peer review, thematic reviews, and consistency checks-to ensure embedment of high-quality validation practices. Executive Reporting & Model Risk Insights Deliver clear, actionable reporting on key model risks, model uncertainty, issue remediation, and emerging trends to senior committees and executives. Support the development and enhancement of divisional and enterprise model quality scorecards and contribute to the risk appetite process Senior Stakeholder, Regulatory & Audit Engagement Serve as a primary point of contact for regulators, internal audit, and senior leaders on model validation related matters Articulate validation rationales, modeling assumptions, and risk implications clearly and confidently to supervisory authorities and executive stakeholders. Qualifications Advanced degree in technical field (e.g. Master's or doctoral degree in quantitative discipline such as Mathematics, Statistics, or Economics). 10+ years of experience across model development, model validation, and model risk management, including a minimum of five years leading multi layered model validation teams. Extensive experience with a broad range of model types, including machine learning/LLM based models. Deep knowledge of model risk management principles and regulatory frameworks (e.g., SR26-2, SS1/23) and demonstrated experience engaging with regulators and internal audit. Strong technical proficiency with programming languages and analytical tools such as Python, R, or C++, and familiarity with emerging technologies, AI governance, and modern model development practices. Proven ability to translate complex technical concepts into clear, actionable insights for senior executives. Exceptional written and verbal communication skills, including experience presenting to senior committees, executives, and regulatory bodies. Demonstrated ability to partner with stakeholders to balance effective challenge, practical solutions, and business objectives. Special Factors Sponsorship Vanguard is not offering visa sponsorship for this position. About Vanguard At Vanguard, we don't just have a mission-we're on a mission. To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best. How We Work Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.
hackajob is collaborating with Vanguard to connect them with exceptional professionals for this role. Overview The Head of Validation, Model Risk is a senior leadership role responsible for setting enterprise direction for model validation-delivering independent, risk-based oversight across a diverse portfolio of models spanning investment and risk management, fraud and compliance, finance and HR, and rapidly evolving Gen AI and agentic use cases. This role serves as the senior authority for model validation, setting the bar for defensible methodologies, rigorous challenge, and clear, decision-ready risk communication to senior leaders. The Head of Validation will strengthen model risk culture and lifecycle discipline across the enterprise-driving timely issue remediation, elevating validation quality and consistency, and ensuring Vanguard's practices remain aligned with regulatory and audit expectations. Responsibilities Leadership & Team Management Leads a high performing, multidisciplinary model validation team responsible for validating a diverse portfolio of models including investment and risk management, fraud and compliance, finance and HR, as well as Gen AI and Agentic use cases Develop and mentor talent to promote strong technical capabilities and a high-quality validation process Validation Oversight & Approval Serve as the final approval authority for validation reports on higher-risk models Ensure validation conclusions are robust, well supported, and communicated clearly to stakeholders with varying levels of technical expertise Model Risk Governance & Lifecycle Management Oversee adherence to enterprise model lifecycle requirements-including model inventory accuracy, change management, ongoing monitoring, and issue remediation. Drive timely resolution of model related issues and non compliance, escalating when necessary Strengthen model risk culture across the enterprise through targeted training, outreach, and proactive engagement with model owners and developers Methodology & Practice Leadership Define, maintain, and continually enhance the methodologies and test approaches used in model validation Ensure comprehensive assessment of conceptual soundness, performance, data quality, implementation accuracy, and other model risk considerations Lead the evolution of validation techniques for emerging modeling approaches, including LLM enabled and agentic systems Standards, Policies & Quality Assurance Own the enterprise's model development and model validation standards, guidelines, procedures, and templates. Establish and oversee quality assurance mechanisms-including peer review, thematic reviews, and consistency checks-to ensure embedment of high-quality validation practices. Executive Reporting & Model Risk Insights Deliver clear, actionable reporting on key model risks, model uncertainty, issue remediation, and emerging trends to senior committees and executives. Support the development and enhancement of divisional and enterprise model quality scorecards and contribute to the risk appetite process Senior Stakeholder, Regulatory & Audit Engagement Serve as a primary point of contact for regulators, internal audit, and senior leaders on model validation related matters Articulate validation rationales, modeling assumptions, and risk implications clearly and confidently to supervisory authorities and executive stakeholders. Qualifications Advanced degree in technical field (e.g. Master's or doctoral degree in quantitative discipline such as Mathematics, Statistics, or Economics). 10+ years of experience across model development, model validation, and model risk management, including a minimum of five years leading multi layered model validation teams. Extensive experience with a broad range of model types, including machine learning/LLM based models. Deep knowledge of model risk management principles and regulatory frameworks (e.g., SR26-2, SS1/23) and demonstrated experience engaging with regulators and internal audit. Strong technical proficiency with programming languages and analytical tools such as Python, R, or C++, and familiarity with emerging technologies, AI governance, and modern model development practices. Proven ability to translate complex technical concepts into clear, actionable insights for senior executives. Exceptional written and verbal communication skills, including experience presenting to senior committees, executives, and regulatory bodies. Demonstrated ability to partner with stakeholders to balance effective challenge, practical solutions, and business objectives. Special Factors Sponsorship Vanguard is not offering visa sponsorship for this position. About Vanguard At Vanguard, we don't just have a mission-we're on a mission. To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best. How We Work Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.