Financial Risk Analytics – Senior Product Analyst

Senior Product Analyst – London

Financial Risk Analytics provides products and solutions to financial institutions to measure and manage market risk, counterparty credit risk, regulatory risk capital, and derivative valuation adjustments.

Using a fully vectorised pricing library, Machine Learning, and a Big Data stack for scalability, our solutions are used by the largest tier‑one banks as well as smaller niche firms.

The products are available as deployed, cloud‑based, or run‑as‑a‑service, freeing up internal resources to focus on business priorities.

About the Role

The role will focus on workflow design, data pipeline requirements, integration patterns, validation controls, and operational improvements that support scalable risk analytics delivery.

Responsibilities

The Senior Product Analyst will work with product, financial engineering, data, technology, support, professional services, and client‑facing teams to analyse requirements and design robust workflows for market data ingestion, enrichment, validation, transformation, integration, and delivery into Risk Analytics products and services.

The role will translate business, analytical, and operational needs into clear specifications, data mappings, process flows, user stories, acceptance criteria, test scenarios, release notes, and operational documentation.

The role will support the design and continuous improvement of data pipelines, APIs, integration services, controls, monitoring, observability, exception management, and automation across Market Data and Integration workflows.

It will investigate complex data and workflow issues using SQL, Python, logs, dashboards, and source‑system analysis; support UAT, regression testing, release readiness, production validation, defect triage, and post‑release monitoring; and act as a senior subject‑matter expert for internal stakeholders and client‑facing teams on data flows, dependencies, constraints, and expected behaviour.

All employees are required to work from the office a minimum of two days per week.

• Required Experience
• Senior experience as a product analyst, business analyst, data analyst, implementation analyst, risk technology analyst, or a similar role within financial services, market data, or analytics technology.
• Strong understanding of market data, reference data, pricing data, data quality, lineage, data controls, and integration workflows.
• Mandatory experience analysing and documenting data pipelines, APIs, batch processes, event‑driven workflows, databases, file‑based interfaces, or cloud‑based data platforms.
• Ability to write clear functional specifications, data mappings, user stories, acceptance criteria, test scenarios, and operational documentation.
• Hands‑on capability with SQL and Python for data investigation, validation, reconciliation, prototyping, automation, or issue analysis.
• Essential knowledge of key financial instruments and risk analytics concepts, including bonds, equities, credit default swaps, market risk, sensitivities, Va R, stress testing, curves, scenarios, pricing inputs, and model data requirements.
• Experience working with Agile delivery teams and collaborating across product, engineering, QA, support, financial engineering, and client‑facing functions.
• Excellent analytical, communication, and problem‑solving skills, with the ability to explain complex data flows and operational issues clearly to technical and non‑technical stakeholders.
• Background in Finance, Economics, Mathematics, Computer Science, Engineering, Data Science, or a related quantitative discipline.
• Preferred Experience
• Experience with Risk Analytics, Buy‑Side Risk, Traded Market Risk, XVA, CCR, FRTB, portfolio risk, fixed‑income analytics, securitised products, liquidity risk, or managed risk‑as‑a‑service solutions.
• Familiarity with Snowflake, Databricks, Spark, AWS, Azure, Confluence, Azure Dev Ops, Git, Tableau, Power BI, message queues, or comparable tools and platforms.
• Knowledge of market data vendors, data mastering, golden‑source design, curve construction, historical market data, pricing services, scenario generation, or analytics input validation.
• Experience with observability, production support, automated controls, regression testing, reconciliation, model input validation, machine learning, NLP, or responsible AI applications in financial analytics.
• CFA, FRM, CQF, or other relevant professional qualification.
• Interview Process

Final‑stage candidates are required to attend at least one in‑person interview, ordinarily at the nearest S&P Global office, before an offer can proceed.

Equal Opportunity Employment

S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race, ethnicity, colour, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law.

Only electronic job submissions will be considered for employment.

If you need an accommodation during the application process due to a disability, please send an email to EEO.

Compliance@spglobal. com.

#J-18808-Ljbffr