Location: Paya Lebar
Office hours: Monday to Friday
The Data Scientist in the Data Strategy and Analytics Division (DSAD) reports to the Principal Manager and plays a pivotal role in deriving business insights from large and real-time datasets for fraud and risk management, strategic planning as well as operational efficiency.
Data Analysis & Model Development
- Research and develop statistical and machine learning models for comprehensive data analysis
- Utilize algorithms and models to mine big data, perform data and error analysis, and ensure data uniformity and accuracy
- Apply data mining techniques and perform statistical analysis to generate insights at scale
Collaboration & Solution Development
- Work closely with both internal and external stakeholders to understand analytic needs and develop effective solutions
- Create machine learning-based tools or processes, such as recommendation engines, and monitor their performance through A/B testing and predictive capabilities
- Communicate analytic solutions to stakeholders and implement necessary improvements to operational systems
Innovation & Capability Building
- Identify relevant structured and unstructured data sources for mining meaningful insights
- Build prototype analysis pipelines iteratively to provide scalable insights
- Contribute to building data analytics capabilities across the organization, emphasizing the strategic value of data in achieving business objectives
What we are looking for:
- Tertiary qualification in a quantitative discipline such as Computer Science, Economics, Statistics, or Applied Mathematics.
- 3-8 years of experience in computer science, applied mathematics, or other quantitative/computational disciplines.
- Proven experience in data visualization tools (e.g., Tableau) and data analysis/processing tools (e.g., R, Python).
- Experience with Cloud Technology (e.g., AWS data and analytics Tech Stack) and distributed computing tools (e.g., Hadoop/Spark).
- Demonstrated ability in building machine learning models at scale, using real-time data pipelines on platforms.
- Strong analytical skills with the ability to communicate complex quantitative analysis in a clear, precise, and actionable manner.
- Proficiency in data engineering, including SQL and manipulating structured and unstructured data sources for analysis.
- Advanced skills in pattern recognition and predictive modeling.
- Experience or specialization in fraud prevention/detection, compliance, forensics, or Jobs and Skills related analysis will be considered advantageous.
- Excellent communication and presentation skills, with a strong emphasis on collaboration and innovation.
Should you be interested in this position, please contact Juliana at 9230 6374 your resume directly for fast respond.
We regret to inform that only shortlisted candidates will be notified.
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