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.
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.