Data Scientist (4-10 yrs)

Role summary:

We are looking for an individual with exceptional logical thinking, emotional intelligence, and a real hunger to achieve to join our Risk Analytics team. The primary job scope is to leverage data using both human and artificial intelligence to achieve a business edge, whether in increasing revenues, saving money or reducing risk.

Responsibilities:

- Build, test, launch, and keep enhancing advanced analytics models to augment internal decision-making processes using internal and external data.

- Develop targeted bespoke analytics models to help the venture 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.

- Research, design, implement and validate analytical tools to achieve or improve targeted outcomes such as bringing predicted outcomes closer to experience while ensuring consistency with the model ecosystem.

- Collaborate with technology teams in setting up an effective model lifecycle platform on the cloud.

- As part of context building, opportunities to contribute to initiatives beyond the analytics area will also be offered.

Role specific technical competencies:

- At least four years' experience in a predictive analytics or Artificial Intelligence / Machine-learning role, or in modelling complex systems.

- Experience in statistical and predictive modelling concepts, machine-learning approaches, clustering and classification techniques, and recommendation and/or optimization algorithms.

- Experience in analytical programming with a focus on Python and in data handling.

- Strong communication skills including ability to write down or explain modelling methodology and decisions clearly to non-technical audiences.

- Understanding of trade and supply chain concepts would be advantageous.

Qualifications (training, licences, memberships, and certifications):

Confidential:

- Strong degree or postgraduate qualifications in any discipline with substantial quantitative component (e.g. Physics, Mathematics, Statistics, Actuarial Sciences, Biostatistics, Meteorology, etc.).

- Professional certifications in data science would be advantageous.