Head of Risk & Decisioning

About Olea:

Olea is a digital infrastructure platform that connects global liquidity with trade and supply chain opportunities, fueling growth and unlocking potential worldwide.  Olea has diverse liquidity pools with varying appetite and focuses.  Olea’s vision is to connect capital to opportunity. It has a strong conviction in the role of trade to support sustainable economic development across countries, particularly emerging markets, particularly Asia where many smaller suppliers are based. Olea supports suppliers and buyers in over 70 corridors.

Role summary:

We are seeking a highly analytical, commercially minded and technically fluent leader to establish and lead Olea's Risk & Decisioning function.  In this role, you will lead the evolution of Olea's decision infrastructure: from traditional quantitative credit risk models and analytical tools through to AI-native decision-support systems. The role is accountable for improving the quality, consistency, speed and transparency of decisions across Olea's pre-trade, at-trade and post-trade workflows.  The Head of Risk & Decisioning will partner closely with the CRO, Commercial, Legal, Compliance and Operations stakeholders while working closely with Product Engineering, Data & AI Operations and other tech teams to ensure that Olea's data, models and AI agents are translated into measurable business impact while remaining explainable, auditable and aligned to risk appetite.

Responsibilities:

• Leadership: Establish and lead the Risk & Decisioning unit (within Technology) serving as the product owner translating CRO-defined risk appetite, product requirements and expert judgement into scalable risk controls. Move fluidly between policy interpretation, model design, data requirements, AI-agent evaluation, implementation and executive communication.

• Trusted decisioning infrastructure. Combine risk expertise, quantitative methods with operating discipline to build a trusted decision layer for Olea. Establish standards governing the methodology, validation, governance and performance expectations of Olea’s risk analytics applications including Olea’s proprietary credit risk models.  Own the design, requirements, development and continuous improvement of Olea’s emerging AI agent workforce encompassing risk, legal, compliance and commercial decision-support agents. 

• Governance & controls. Ensure every model, agent and decision the team produces is traceable, explainable, auditable and designed to support accountable, human decision-making.
  Define success measures, controls and escalation pathways for each agent. Establish lifecycle standards for model and agent development.

• Cross-team collaboration & value realisation. Partner closely with business stakeholders and provide direction to Product Engineering and Platform teams to ensure decisioning capabilities are implemented, operationalized, monitored and continuously improved in production. Operate with a product lens, translating business priorities into roadmaps, adoption and measurable business outcomes.

• Technical mentoring & culture. Guide and support risk & engineering colleagues to develop the next generation of data science & AI engineering talent.  Mentor and guide colleagues to elevate data and AI literacy across the organization.

Role specific technical competencies:

• Leadership & industry experience: 8+ years of experience building analytical products, machine learning or AI-enabled capabilities that delivered measurable business outcomes preferably within financial services, transaction banking, fintech, or trade finance. Domain expertise in credit, counterparty and structural risk across cross-border trade, supply chain finance, invoice financing or factoring is an advantage.
• Technical excellence. Hands-on experience developing & implementing credit risk models (PD, LGD, EAD), risk analytics solutions and/or other AI-enabled decision-making capabilities. Strong understanding of statistical modelling, machine learning, model governance and modern AI evaluation approaches including governing AI agents and agentic workflow is required.  Experience with fraud detection, anomaly monitoring and/or use of alternative data sources is an advantage. 
• Engineering capabilities. Strong proficiency in Python, SQL and modern data engineering practices. Familiarity with AI-native workflows and building applications using technologies such as TypeScript, FastAPI, Postgres and Docker on cloud-native platforms is strongly preferred.  Experience deploying models in a production environment is an advantage.
• Communication skills. Exceptional communication skills, including the ability to document and explain modelling methodology, AI capabilities, limitations and business implications clearly, concisely and in an actionable manner to non-technical audiences.
• People leadership. Experience leading or mentoring small technical or analytical teams.

Qualifications (training, licences, memberships and certifications):

• An advanced degree (or a bachelor’s degree with first class honors) in a quantitative discipline such as Data Science, Statistics, Biostatistics, Mathematics, Actuarial Science, Finance, Economics or a related field of study.

Note:

Olea is committed to diversity and inclusion. By providing equal opportunities we foster a work environment which embraces diversity and gets the best out of the broadest spectrum of people to sustain business performance and competitive advantage. We build an inclusive culture by demonstrating respect for each other’s unique strengths and perspectives to enable every employee to develop a sense of belonging and have the opportunity to maximise their potential.