Data Scientist - Geylang
ScienTec Consulting Geylang Temporary
Working Hours: Monday – Thursday (8.30am – 6pm), Friday (8.30am – 5.30pm) (Hybrid working arrangement)
Working Location: Central
Working Location: Central
Salary Package: Up to $10k
We are seeking a Data Scientist with strong expertise in applied machine learning, data science, and software engineering. The successful candidate will design, build, and deploy scalable ML models to power intelligent data-driven products and solutions.This role requires a combination of hands-on technical proficiency, problem-solving ability, and collaboration with cross-functional teams to deliver impactful and production-ready machine learning systems.
Responsibilities:
- Design, train, and evaluate machine learning models for diverse use cases such as prediction, classification, and generation.
- Conduct experiments to assess model performance and identify opportunities for improvement.
- Tune hyperparameters, refine architectures, and propose new modeling strategies to enhance model accuracy, scalability, and robustness.
- Collaborate with software engineers and product teams to build ML-driven product features such as recommendation engines, anomaly detection, or data analytics components.
- Develop and optimize data preprocessing pipelines and implement effective feature engineering strategies.
- Diagnose and troubleshoot issues related to model training, deployment, or data quality.
- Work closely with engineers to resolve integration challenges and ensure reliable model performance in production environments.
- Document model architectures, parameters, and evaluation metrics for internal and user-facing reference.
- Communicate complex ML concepts in a clear and accessible way to both technical and non-technical audiences.
- Work closely with software engineers to integrate ML models into production systems using APIs or microservices.
Requirements:
- Bachelor’s degree or higher in Computer Science, Data Science, Artificial Intelligence, Statistics, or related fields.
- Proficiency in Python and strong knowledge of ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
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This authorizes us to:
- Contact you about potential opportunities.
- Delete personal data as it is not required at this application stage.
- All applications will be processed with strict confidence. Only shortlisted candidates will be contacted.
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