About the Company

Olea, a digital infrastructure platform majority-owned by Standard Chartered and incubated within Standard Chartered Ventures, directs global liquidity to supply chain and trade assets. Leveraging advance technology, Olea provides financing solutions to global supply chain participants, empowering sustainable trade and supporting sustainable economic development. Headquartered in Singapore, Olea’s business spans 70+ trade corridors globally, predominantly Asia-linked.

The Opportunity

We are seeking a highly analytical and driven individual to join our Risk Analytics team. This role is ideal for someone with strong logical thinking, emotional intelligence, and a passion for using data to drive business outcomes. You will play a key role in building advanced analytics capabilities to enhance decision-making and deliver business impact whether in increasing revenues, saving money or reducing risk.

What you will be doing:

• Conduct quantitative analysis to support the CRO in building data-driven risk management processes.
• Design, build and implement analytical tools to automate manual data-intensive workflows.
• Build, test, launch and continuously enhance existing predictive models to augment internal decision-making processes using internal and external data.
• Develop bespoke analytics models to help Olea extract value from, and monetise, data on our platforms, where such value extraction could include the likes of better client decisioning, pricing and opportunity identification.
• Create dashboards and other reporting tools to deliver insights efficiently and at scale.
• Collaborate with technology teams to maintain & enhance the quality of data on our platforms; and to integrate analytical tools into production environments.
• Mentor and guide data analytics colleagues to elevate data literacy across the organization.
• Contribute to initiatives beyond the analytics area.

What you'll need to be successful in the role:

• 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.
• 8+ years of experience in risk analytics, a predictive analytics / Machine-Learning role, and/or in modelling complex systems.
• Hands-on experience in building credit risk models, performing quantitative risk analysis and familiarity with common techniques (e.g. building scorecards, Monte Carlo simulations, etc.).
• Strong proficiency in analytical programming with a focus on Python, SQL and strengths in data handling.
• In-depth knowledge of statistical and predictive modelling concepts, machine-learning approaches, clustering and classification techniques, and recommendation and/or optimization algorithms.
• Strong communication skills including the ability to write down; and explain modelling methodology and decisions clearly to non-technical audiences.
• Independent, self-driven, detail-oriented, and comfortable working in a fluid, ever-changing environment.
• Experience working with any of the following datasets would be highly advantageous: corporate and SME data, transaction and payment records, fraud and anomaly detection data, and alternative data sources for credit risk modeling and fraud detection (e.g. mobile data, geolocation data, utility payment data, social media, negative news and public records, etc.)
• Understanding of trade and supply chain concepts would be advantageous.
• Technical skills in working with AWS cloud platform and data visualizations tools are a plus.

Equal Opportunity Statement

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.