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全职 Data Scientist 工作, 薪水, Epergne Solutions 公司招聘中 - Ricebowl

Data Scientist

Epergne Solutions

Singapore

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工作地点

  • Singapore

职位描述

岗位职责

Job Role: Data Scientist

Experience: 3–5 Years

Location: Singapore

Role Overview

We are looking for a Data Scientist with hands-on experience in Python, SQL, predictive modelling and fraud or risk analytics. The role involves enhancing fraud detection models, reviewing model methodologies and thresholds, building monitoring dashboards, and assessing new schemes for potential fraud risks.

Key Responsibilities

  • Review and recalibrate model methodologies and thresholds through back-testing, validation and performance analysis.
  • Enhance fraud-risk models by developing features, indicators, risk scenarios and analytical logic.
  • Build and maintain technical dashboards to monitor model performance, data drift and concept drift.
  • Evaluate new schemes, identify potential fraud patterns and recommend suitable risk coverage.
  • Analyse complex datasets, investigate anomalies and ensure data quality and reliability.
  • Define performance metrics, alert thresholds and monitoring approaches.
  • Maintain technical documentation, analytical specifications and model change records.
  • Communicate analytical findings and recommendations to technical and business stakeholders.
  • Develop reproducible code and support the deployment and maintenance of analytical solutions.

Mandatory Skills

  • Strong hands-on experience in Python and SQL.
  • Experience in data science, predictive modelling, fraud detection, risk scoring or anomaly detection.
  • Knowledge of feature engineering, back-testing, threshold calibration and model validation.
  • Experience evaluating model performance using precision, recall and related metrics.
  • Ability to translate business requirements into analytical specifications, model rules and risk indicators.
  • Experience working with large datasets, data quality checks, anomaly investigation and analytical documentation.

Preferred Skills

  • Experience with imbalanced datasets and delayed or incomplete outcome labels.
  • Knowledge of data drift, concept drift and production model monitoring.
  • Experience building dashboards using Tableau or similar tools.
  • Exposure to CI/CD, MLOps and model deployment.
  • Experience with Spark/PySpark, AWS Redshift or AWS Glue.
  • Knowledge of network or graph analytics.
  • Experience with grants, claims, workforce, training or regulatory datasets.

Educational Qualification

Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics or a related quantitative discipline

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