Responsibilities
- Actively seek out opportunities to innovate by using non-traditional data and new modelling techniques fit for purpose to the needs of our clients
- Enhance existing analytic techniques by promoting new methodology and best practices in analytics field
- High interaction with external clients, and manage internal and external stakeholders
- Create and monitor dashboards (Power BI and Tableau) and reports for relevant projects.
- Define detailed scope and methodology, creating and executing on the framework with appropriate data mining techniques
- Building data science visualization capabilities to solve client's problems
- Drive innovation through using data science techniques
- Act as data science advocate within our client, advising and coaching analytical teams and sharing best practices and case studies.
- Continually look at the environment to challenge our assumptions around new sources of data, potential analytics partners, tools, talent and infrastructure.
- Explore leading methodologies and best practices to other teams and importing successful methodologies from other international markets
Qualifications
We are looking for a motivated, analytical minded individual with a track record of using data science and analytics expertise to unlock business value. A successful candidate should have accumulated a variety of industry experience and have solid background in mathematic / statistic.
- Degree in Quantitative field such as Statistics, Mathematics, Operational Research, Computer Science, Economics, or engineering or equivalent
- Experience in performing data exploration and feature experience engineering
- Experience in Credit Risk Analytics and Digital Marketing Analytic would be an added benefit
- Deep analytical expertise in applying statistical solutions to business problems
- Proficiency with modelling software, experience with Python, R, SAS, Matlab,or similar instruments
- Practical experience in building and applying machine learning models (regression, clustering, classification: gradient boosting, random forests, linear models, deep learning etc.), understanding in how these algorithms work and end-to-end development skills from business understanding and data preparation to quality assurance of ML models
- Demonstrated ability to innovate solutions and solve business problems capabilities
- Excellent presentation skills, including strong oral and written
- Self-motivated, results-oriented individual with the ability to progress multiple priorities concurrently
