Director, Knowledge Graph and Entity Infrastructure

Connected Analytics and Risk

• Translate the unified analytics framework into a practical semantic model. Define analytical domains, subjects, lenses, capabilities, methods, inputs, outputs and the relationships among them so teams can understand and reuse work across products.
• Model the connections that can explain risk pathways, such as how a country or industry development may relate to companies, exposures and credit outcomes. Make the meaning, timing, source and limits of each relationship explicit.
• Work with data scientists to test whether graph relationships, features or algorithms improve a priority model or analytic use case. Compare the result with a simpler baseline and retain what proves useful.

Implementation and Partnership

• Embed in selected initiatives and personally build initial graph models, data mappings, queries and working implementations. With engineering and Core platform teams, develop the ingestion, validation and interfaces needed to make successful solutions reliable.
• Use shared entity and identifier services as they mature. When a use case exposes a genuine linking problem, work with the teams that own entity resolution to define requirements and test an appropriately simple solution.
• Establish reusable modeling patterns, examples and quality measures for relationships, provenance, temporal context and coverage. Teach partner teams to use and extend the capability, and help shape a larger specialist team if demand supports it.

Your First Year:

Initial priorities will be chosen in collaboration with the Head of Analytics and product teams based on client value and available data. Early outcomes should include:

• A working implementation for one priority analytics or risk question, using real data and a model validated with domain experts and prospective users.
• A test of at least one adjacent use case, such as graph-derived features for a model or connected research for source-backed AI, measured against a simpler approach.
• Reusable patterns, working examples and a practical adoption plan so future squads can apply what proves useful, with clear responsibilities across the Data Science Engine, Core platform and content teams.

You May Be a Good Fit If:

Strong candidates may come from knowledge graph engineering, data engineering, applied data science or semantic technology. We care more about what you have built and how you approach a problem than a particular tool stack or formal ontology background.

• You have built a knowledge graph or another connected data application for analytics, content or AI, and can take an idea from domain conversations to a working implementation.
• You are a hands-on builder with Python and SQL who can own data mappings, graph queries, tests and the first usable version of a solution.
• You can model real-world relationships with appropriate attention to identity, time, provenance and validation, adding detail as the use case requires it.
• You have experience with a graph database or query language, or closely related semantic tooling. Familiarity with Cypher, SPARQL, RDF or property graphs is valuable; no single stack is required.
• You can work with analysts, product managers, data scientists and engineers to define an ambiguous problem, make practical tradeoffs and deliver something other teams can use.

What Would Make You Stand Out:

• Knowledge of credit, financial markets, industry or country risk data, or experience making complex research content usable as structured information.
• Experience applying graph-derived features to modeling, or connected retrieval to source-backed AI applications.
• Experience with content enrichment, taxonomy design, temporal data, provenance or linked data standards across multiple teams or source systems.

What We Offer

• A build from first principles rather than the maintenance of an inherited system.
• An opportunity to establish a new specialist capability within the Data Science Engine and shape how Fitch Solutions connects its analytics and research.
• A hands-on remit spanning risk analytics, data science and AI, with close access to product teams and domain experts.
• Scope to test useful approaches with real use cases before scaling them across a wider portfolio.

Why Choose Fitch:

• Hybrid Work Environment: 3 days a week in office required based on your line of business and location
• A Culture of Learning & Mobility: Dedicated trainings, leadership development and mentorship programs designed to ensure that your time at Fitch will be a continuous learning opportunity
• Investing in Your Future: Retirement planning and tuition reimbursement programs that empower you to achieve your short and long-term goals
• Promoting Health & Wellbeing: Comprehensive healthcare offerings that enable physical, mental, financial, social, and occupational wellbeing
• Supportive Parenting Policies: Family-friendly policies, including a generous global parental leave plan, designed to help you balance career and family life effectively
• Inclusive Work Environment: A collaborative workplace where all voices are valued, with Employee Resource Groups that unite and empower our colleagues around the globe
• Dedication to Giving Back: Paid volunteer days, matched funding for donations and ample opportunities to volunteer in your community

At Fitch, AI is embedded in how we work every day—supporting smarter decision-making, streamlining workflows, and enabling new ways to create value for our business and clients. Intelligent solutions are increasingly part of our day-to-day operations, helping teams work more efficiently and think differently as we continue to evolve. We’re looking for colleagues who are comfortable operating in an AI-enabled environment—or who are curious, adaptable, and eager to build their AI literacy over time. We value professionals who embrace technology as part of continuous learning and who are committed to using it thoughtfully to enhance how work gets done.

Fitch is committed to providing global securities markets with objective, timely, independent and forward-looking credit opinions. To protect Fitch’s credibility and reputation, our employees must take every precaution to avoid conflicts of interest or any appearance of a conflict of interest. Should you be successful in the recruitment process at Fitch Ratings you will be asked to declare any securities holdings and other potential conflicts prior to commencing employment. If you, or your immediate family, have any holdings that may conflict with your work responsibilities, you may be asked to divest yourself of them before beginning work.

Fitch is proud to be an Equal Opportunity and Affirmative Action Employer. We evaluate qualified applicants without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, disability, protected veteran status, and other statuses protected by law.