The Role:
The Team:
A full-scale microservices transformation of the S&P Globals Financial Risk Analytics product, pre-AI, was expected to require a large pool of technology roles across architecture, engineering, platform, security, operations, and delivery.
For the initial FRA prototype transformation, we want to stand up a lean, generative-AI enabled transformation squad with a focused team structure sized to deliver a validated microservices foundation.
The objective is to establish an agile technology transformation group to design and deliver a commercially aligned, targeted microservices architecture for the FRA platform, prioritizing measurable business outcomes and rapid learnings.
Responsibilities and Impact:
- Lead the quality assurance of transformed financial services by establishing rigorous automated testing frameworks that ensure correctness, regulatory compliance, and data integrity.
- Develop comprehensive integration, regression, and scenario testing to validate service outputs, pricing models, algorithms, and statistical results, safeguarding analytical accuracy.
- Drive regulatory compliance by ensuring auditability, supporting model governance, and embedding controls that meet financial industry standards and controls frameworks.
- Design and execute stress testing and risk scenarios to identify vulnerabilities, ensure resilience, and maintain confidence in critical financial calculations and models.
- Collaborate closely with risk, compliance, and audit teams to embed validation processes that support transparency, traceability, and regulatory reporting requirements.
- Join a transformation journey where your expertise ensures that innovative financial services are reliable, compliant, and built on a foundation of rigorous quality assurance.
What We’re Looking For:
Key qualifications for the job
- Good to have CFA/FCM qualification with a strong quantitative analysis capability
- Python / SQL
- Automated testing framework design (with experience in generative-AI development)
- Financial modelling
Key soft skills
Attention to detail and precision
— Ensuring regulatory compliance, data integrity, and model accuracy requires meticulousness and a thorough approach.Strong analytical and critical thinking
— Ability to interpret complex financial models, identify risks, and validate outputs effectively.Effective communication and collaboration
— Working with product, compliance, audit, and technical teams to ensure transparency, traceability, and regulatory adherence.Resilience and problem-solving under pressure
— Handling high-stakes validation and testing scenarios, especially during audits or regulatory reviews, with calm and confidence.
Additional key qualifications for the job
- Capital markets
- Risk analytics
- Investment systems
- Model validation
Additional soft skills
Industry acumen and contextual understanding
— Deep knowledge of capital markets, risk analytics, and investment systems to interpret complex models and ensure relevance.Critical thinking and judgment
— Ability to assess model validity, identify potential biases, and evaluate risk implications with sound judgment.Effective stakeholder engagement
— Communicating complex validation results clearly to non-technical stakeholders, including front-office, risk managers, and regulators.Adaptability and continuous learning
— Staying current with evolving financial regulations, market practices, and modeling techniques to ensure ongoing compliance and accuracy.
