Data Scientist

5 days ago

Singapore The Edge Asia Full time

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.

EA License: 16S8131

Recruiter License: R22104669

**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.
- 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.
- Working knowledge in Fraud Risk Management, Conduct and Financial Crime Compliance domains in Bank.

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