Senior Data Scientist - Toa Payoh

We are looking for a Senior Data Scientist to join our Kpler’s Flows team. This role is critical in developing algorithms that extend our comprehension of commodities flows in space and time by devising forecasting models, predicting future trades, detect anomalies in data and anomalous behaviour of various players.

Key Responsibilities:

• Devise efficient solutions to tackle ML/Big Data challenges using relevant, up-to-date methods and technologies.
• Work across the stack to deliver new features end-to-end, from prototyping, to deployment and caring for data drift in production.
• Ensure optimal, cost-effective design decisions that improve performance and overcome scalability limits.
• Own meaningful parts of our service, demonstrating the ability to lead projects independently, have an impact, and grow with the company.
• Identify opportunities for novel projects and liaise with product teams to advance ideas into value-adding features.
• Actively share knowledge and document insights, effectively communicate complex concepts and analysis to technical and non-technical audiences, aiming to support continuous team improvement and drive collaboration.
• Act as a mentor for our junior data scientists, helping to accelerate their growth; you will act as the Tech Lead on some projects.
• Be part of a vibrant Machine Learning community in Kpler, tackling the whole spectrum of ML problems.

Requirements:

• You have at least 5 years of experience in the DS role, deploying models into production;
• You have proven experience delivering end-to-end ML solutions that produce business value.
• You are proficient in Python.
• You have expert knowledge of at least one cloud computing platform (preferably AWS).
• You are fluent in English.
• You have expertise on applications focusing on geospatial data and mobility analytics (highly desirable).
• You have proven experience with big data technologies, specifically Spark and Kafka.
• You have experience working with state-of-art ML pipeline technologies (such as MLflow, Sagemaker...) or building a ML pipeline by yourself (Docker, Kubernetes, Paperspace, Airflow...).
• You are familiar with the shipping industry and commodity trading.
• You are comfortable with software engineering best practices.
• You value code simplicity, performance and attention to detail.
• You have experience working in an international environment.