Job Description
- Train and optimize predictive and machine learning models to solve business problems.
- Perform ad-hoc statistics and data mining tasks on diverse datasets.
- Enhance data collection procedures to improve analytic systems.
- Develop prototypes and advanced analytics capabilities to derive actionable insights.
- Design and build visualization interfaces to aid decision-making.
- Stay up-to-date with the latest advancements in data science research.
- Test and evaluate new tools and packages.
- Support the transition to a data-driven culture within the company.
- Identify, analyze, and present data discovery outputs for analytic projects.
- Develop data ingestion pipelines and create analytic data assets.
- Collaborate with data engineers to enhance the analytic data infrastructure.
Job Requirements
- PhD/Masters/Bachelor's in Computer Science, Statistics, Applied Mathematics, or related disciplines.
- Strong understanding of machine learning techniques and algorithms.
- Proficiency in data wrangling, transformation, and feature engineering using programming tools such as Spark, Python, or R.
- Experience with common data science toolkits and visualization tools.
- Familiarity with SQL and query languages.
- Excellent communication and presentation skills in English.
- Taste for working in teams, self-starter, able to work on multiple projects in parallel Industry experience in data analytics working in a big data environment.
- Familiarity with Commercial or Institutional Banking use-cases is preferred but not necessary.
Kindly be informed that only shortlisted candidates will be notified.
