Senior Data Scientist

Role & Responsibilities The Senior Data Scientist will be responsible for developing production-ready data and ML solutions and supporting the design of the underlying data platform.

• Work closely with the data engineering team to design and build data pipelines and backend services for data ingestion, processing, and access across the platform.

• Develop, deploy, and maintain data models and ML models, ensuring they are production-ready and aligned with platform use cases.

• Assess available data and formulate hypotheses for potential data science and ML use cases, helping inform data collection and architecture decisions.

• Conduct hypothesis testing across candidate use cases to identify opportunities for further development.

• Collaborate with the data team on the analytics layer, ensuring data models and outputs are accessible and meaningful to downstream consumers.

• Support the ingestion and processing of data from IoT, sensors, robotics, and industrial equipment where applicable.

• Prepare data infrastructure and pipelines to support GenAI, Large Language Model (LLM), and Retrieval-Augmented Generation (RAG) use cases where required.

• Produce technical documentation covering model development decisions, pipeline design, and implementation.

• Work closely with internal teams to progressively transfer data science and ML modelling capabilities.

Requirements

• Degree in Computer Science, Engineering, Data Science, or a related field.

• 8+ years of relevant experience in Data Science and Machine Learning.

• Proven experience developing and deploying data and ML models in production environments at scale.

• Strong experience collaborating with Data Engineers on pipeline design, backend services, and analytics layer development.

• Hands-on experience with modern data platforms such as Databricks or equivalent, deployed on AWS or comparable cloud infrastructure.

• Proven track record leading data science delivery for national-scale or large and complex data platforms, having served as Lead Data Scientist for a significant portion of the project lifecycle.

• Demonstrated experience delivering comparable projects internationally at city-level or above, beyond the Singapore market.

• Familiarity with IoT and industrial messaging protocols such as MQTT, AMQP, and OPC-UA for sensor, robotics, and industrial equipment data ingestion.

• Experience working with robotics data formats, telemetry, field sensors, and equipment data streams is preferred.

• Experience designing ingestion pipelines for robotics or field-sensor data is preferred.

• Experience preparing data infrastructure and pipelines for GenAI, LLM, or RAG workloads is preferred.

• Strong communication and collaboration skills, with the ability to transfer data science and ML knowledge to internal teams.