Senior Data Scientist

ASTEK SINGAPORE INNOVATION TECHNOLOGY PTE. LTD.; Singapore; On-site; SGD 90,000 - 120,000; Full time

Job summary

A leading technology firm in Singapore is seeking a Machine Learning Engineer with at least 8 years of experience to enhance model performance through data feature engineering, conduct cross-validation, and integrate Generative AI tools. The role involves collaborating with cross-functional teams to ensure data quality and model effectiveness. This position offers an innovative work environment with opportunities for growth.

Qualifications

• Min 8 years of experience in related field.
• Proficiency in machine learning model development and evaluation.
• Experience with Generative AI tools.

Responsibilities

• Engineer and extract meaningful features from transaction data.
• Conduct cross-validation and fine-tune model hyperparameters.
• Monitor model outputs for data drift and degradation.
• Collaborate with data engineers and business analysts.

Skills

Machine learning

Dimensionality reduction

Data analysis

Generative AI

Collaboration

Job description

• Min 8 years of experience in related field
• Engineer and extract meaningful features from transaction data to enhance machine learning model performance.
• Perform feature selection and apply dimensionality reduction techniques to optimize computational efficiency and model accuracy.
• Design, develop, train, and evaluate machine learning models leveraging transaction datasets.
• Conduct cross-validation and fine-tune model hyperparameters to maximize performance.
• Continuously monitor model outputs to detect data drift, concept drift, and overall model degradation.
• Establish and maintain automated model retraining and updating workflows to ensure sustained model relevance and accuracy.
• Integrate Generative AI (GenAI) tools and methodologies to streamline transaction monitoring and reduce development cycles.
• Design, test, and refine large language model (LLM) prompts to improve outcome accuracy, consistency, and efficiency.
• Explore opportunities to enhance data science workflows using GenAI capabilities across model development, data analysis, and feature engineering tasks.
• Collaborate with data engineers, software developers, and business analysts to embed data quality monitoring into broader data infrastructure.
• Partner with subject matter experts to align transaction data processing with business logic and compliance requirements.
• Clearly communicate data quality assessments, model results, and project status updates to both technical and non-technical stakeholders.
• Deliver actionable insights and strategic recommendations to improve both data quality and model effectiveness.
• Maintain thorough documentation of machine learning workflows, data preprocessing steps, and GenAI-driven solutions.
• Keep up-to-date with advancements in machine learning, generative AI, and data governance practices.
• Experiment with emerging tools, platforms, and approaches to continuously improve data monitoring and modeling capabilities.