Senior Data Scientist
Summary
Build and deploy production-grade ML models and data pipelines, collaborating with engineers to support IoT, robotics, and GenAI use cases on a large-scale data platform.
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.