jobs in OPTIMUM SOLUTIONS (SINGAPORE) PTE LTD

全职 Junior Data Scientist (Python - Sql) 工作, 薪水 up to SGD 7,800, OPTIMUM SOLUTIONS (SINGAPORE) PTE LTD East Region (Singapore) 公司招聘中 - Ricebowl

Junior Data Scientist (Python - Sql)

OPTIMUM SOLUTIONS (SINGAPORE) PTE LTD

East Region (Singapore)

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工作地点

  • 1 CHANGI BUSINESS PARK CRESCENT East Region (Singapore) Singapore

职位描述

岗位职责

Our client is seeking a Data Scientist to support multiple product squads in redesigning operational workflows and developing AI-enabled solutions. The role focuses on analysing large operational datasets, identifying anomalies and risk patterns, and building machine-learning models to improve decision-making and operational efficiency.

Responsibilities

  • Analyse large operational datasets to identify patterns, anomalies, outliers and potential risk indicators.
  • Develop machine-learning models for anomaly detection, clustering, classification, segmentation and risk scoring.
  • Perform feature engineering using structured and unstructured data, and evaluate model performance using appropriate metrics.
  • Build and maintain scalable data pipelines and deploy production-ready models integrated with applications.
  • Monitor model performance, data quality and data drift after deployment.
  • Collaborate with engineers, product teams and domain experts to translate operational challenges into practical analytical solutions.
  • Apply LLMs and other AI techniques alongside traditional machine-learning approaches where appropriate.
  • Develop reusable analytical solutions and components for application across multiple projects.

Requirements

  • At least 2 years of relevant experience in data science or related field
  • Degree in Data Science, Computer Science, Statistics, Machine Learning, Data Analytics, Information Systems or a related field.
  • Strong proficiency in Python and SQL, with experience analysing large, complex operational or transactional datasets.
  • Hands-on experience in applied data science, including statistical analysis, feature engineering, machine learning and model evaluation.
  • Experience with anomaly detection, classification, clustering, risk modelling or similar techniques.
  • Experience building data pipelines and deploying models into production environments.
  • Familiarity with software engineering practices, including Git, automated testing and APIs

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