Data Scientist (AI/ML)
- Design and develop data pipelines and backend services for data ingestion, processing, and access.
- Build, deploy, and maintain production-ready data science and machine learning models.
- Analyze data to identify opportunities for analytics, AI, and ML use cases.
- Collaborate with data engineering teams on pipeline design and analytics layer development.
- Support hypothesis testing and model validation for business and operational use cases.
- Ensure data models and outputs are accessible and meaningful for downstream applications.
- Document model development, pipeline architecture, and technical decisions.
- Contribute to knowledge sharing and capability development within the team.
Job Role:-
Data Scientist (AI/ML)
Job Location:
- Singapore
Experience:
-8+ Years
Seniority Level:
Senior Consultant
Roles & Responsibilities:-
- Design and develop data pipelines and backend services for data ingestion, processing, and access.
- Build, deploy, and maintain production-ready data science and machine learning models.
- Analyze data to identify opportunities for analytics, AI, and ML use cases.
- Collaborate with data engineering teams on pipeline design and analytics layer development.
- Support hypothesis testing and model validation for business and operational use cases.
- Ensure data models and outputs are accessible and meaningful for downstream applications.
- Document model development, pipeline architecture, and technical decisions.
- Contribute to knowledge sharing and capability development within the team.
Skills & Requirements:-
- Bachelor?s degree in Computer Science, Engineering, Data Science, or a related field.
- 8+ years of experience in data science and machine learning.
- Proven experience developing and deploying ML models in production environments.
- Strong experience with Python, SQL, and modern data platforms such as Databricks or equivalent.
- Experience working with AWS or other cloud-based data and analytics platforms.
- Knowledge of data pipelines, analytics architectures, and MLOps practices.
- Familiarity with IoT, telemetry, sensor, or industrial data processing is an advantage.
- Experience supporting GenAI, large language model (LLM), or retrieval-augmented generation (RAG) workloads is an advantage.