Applied Data Scientist

Newbridge; Singapore; On-site; SGD 90,000 - 120,000; Full time

Job summary

A leading tech firm in Singapore is seeking an experienced Applied Data Scientist to develop and deploy machine learning models that drive business growth. You will work closely with cross-functional teams to identify business problems and integrate models into operations. The ideal candidate has proficiency in Python or Scala, experience with various machine learning frameworks, and knowledge of deployment tools like Docker and Kubernetes. This role offers a collaborative environment focused on innovation and operational efficiency.

Qualifications

• Proficiency in Python and Scala for programming.
• Experience with machine learning algorithms and frameworks.
• Familiarity with deployment tools like Docker and Kubernetes.

Responsibilities

• Develop and train machine learning models using various algorithms.
• Deploy models in production environments ensuring reliability.
• Monitor and maintain models for accuracy and effectiveness.
• Continuously optimize models to improve performance.
• Collaborate with engineers and product managers for integration.
• Document all stages of model development and deployment.

Skills

Python

Scala

Machine Learning Algorithms

scikit-learn

TensorFlow

PyTorch

Docker

Kubernetes

AWS SageMaker

Cloud Technologies

Job description

We're seeking an experienced Applied Data Scientist to join our clients team. As an Applied Data Scientist, you will develop and deploy machine learning models to drive business growth and improve operational efficiency. You will work closely with cross-functional teams to identify business problems, develop predictive models, and integrate them into business operations.

Key Responsibilities:

1. Model Development: Develop and train machine learning models using various algorithms and techniques.
2. Model Deployment: Deploy models in production environments, ensuring scalability, reliability, and performance.
3. Model Maintenance: Monitor and maintain models, ensuring they remain accurate and effective.
4. Model Optimization: Continuously optimize and refine models to improve performance and adapt to changing business needs.
5. Collaboration: Work closely with data engineers, product managers, and other stakeholders to integrate models into business operations.
6. Technical Documentation: Document model development, deployment, and maintenance processes.

Requirements:

Technical Skills:

1. Programming: Proficiency in languages such as Python/Scala.
2. Machine Learning: Experience with machine learning algorithms and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
3. Model Deployment: Familiarity with model deployment tools and platforms (e.g., Docker, Kubernetes, AWS SageMaker).
4. Cloud Experience: Experience with cloud-based technologies (e.g., AWS, Azure, Google Cloud).