int(8531)
Singapore

Data Scientist – Financial Crime Compliance

Our client is a global bank, and their Surveillance Optimization team is looking for a Data Scientist. The role is a permanent position based in Singapore.

Please contact Sophia Lin or email your cv directly in word format with job reference no. Jo0000008029 to corporategovernance@theedgepartnership.com.

Please note that due to the high number of applications only shortlisted candidates will be contacted. If you do not hear from us in the next 5 business days, we regret to inform you that your application for this position was unsuccessful.

EA License: 16S8131

Recruiter License: R22104669

Apply for this Job

Key responsibilities

  • You will be building Statistical/Machine Learning models in either Python, R or PySpark to solve business problems using Advanced Analytics in Predictive and Prescriptive space.
  • You will be presenting results of your analysis and interpreting outputs of your models to give recommendations to the stakeholders.
  • You will be maintaining and documenting produced code and modelling process.
  • You will be working with data engineers to prepare and integrate data from various data sources.
  • You will be helping data engineers and Machine Learning engineers with model deployment.
  • You will be cooperating with (both technical and non-technical) various Bank departments to adjust analytics solution to the business needs.
  • You will be performing data mining, exploration, and analysis.
  • You will be creating data visualizations, reports, dashboards, and data audits.
  • You will Design, train, and implement machine learning algorithms.
  • You will leverage predictive models to optimize customer experiences.
  • You will be creating automated anomaly detection.

Role requirements

  • Minimum 5 years of experience in the data science field with a total experience of 10 years in data, technology, and analytics space.
  • Bachelors or Advanced degree in engineering, finance, accounting, mathematics, or social sciences with excellent quantitative methodological skills.
  • Solid experience in at least one of the following programming languages: Python, R or PySpark.
  • Experience in application of statistics, classification, regression, segmentation, and dimensionality reduction methods and preferably in any of the following data science related areas:
    • Econometrics, time-series analysis, optimization methods, Bayesian statistics, natural language processing.
    • Experience in creating and using advanced machine learning algorithms.
    • Linear regression, logistic regression, decision and regression trees, random forest, boosting algorithms (e.g.: XGBoost), k-means, neural networks, hierarchical clustering, and principal component analysis.
  • Solid understanding and implementation knowledge of the following data science concepts:
    • Bias-variance trade-off, regularization, model evaluation metrics, cross-validation, bootstrapping, hyperparameter tuning, feature selection & feature engineering.
    • Experience in relational databases (Hadoop/HIVE) using SQL.
    • Knowledge of data science toolkits such as R, NumPy, and MATLAB.
    • Experience in data visualization.
    • Expertise in data mining and machine learning.
    • Working knowledge of statistical models and business intelligence.
    • Strong English oral and written communications skills and experience defending research findings.
  • Nice To Have:
    • Experience with version control systems (e.g., GIT/Bitbucket).
    • Experience in Cloud technologies.
    • Experience in ML Ops.
    • Experience with ETL and data engineering.
    • Experience with Spark and other big data technologies.
    • Knowledge of graph databases and knowledge graph applications in data science is a plus (e.g., Neo4j).
    • Working knowledge in Fraud Risk Management, Conduct and Financial Crime Compliance domains in Bank.