Data Scientist (Machine Learning / Data Modeling)

Responsibilities
Design and develop scalable data pipelines and backend services for data ingestion and processing.
Build, deploy, and maintain production-ready data science and machine learning models.
Analyse data to identify opportunities for AI/ML use cases and validate hypotheses.
Collaborate with data engineers to develop data models and analytics solutions.
Document model development, data pipelines, and technical decisions.
Support knowledge transfer and capability building within the team.

Requirements
Degree in Computer Science, Data Science, Engineering, or a related discipline.
8+ years of experience in data science, with a strong track record of delivering production-scale ML solutions.
Hands-on experience with machine learning model development, deployment, and data engineering collaboration.
Experience with modern data platforms (e.g. Databricks) and cloud environments such as AWS.
Proven experience leading data science initiatives for large-scale, complex data platforms.
Knowledge of IoT and industrial messaging protocols (e.g. MQTT, AMQP, OPC-UA).
Experience with robotics, sensor, or industrial data processing is an advantage.
Exposure to GenAI, LLM, or Retrieval-Augmented Generation (RAG) data pipelines is preferred.