Senior Data Scientist

7 days ago


Pretoria, South Africa Fempower Personnel Full time

Our client has an opportunity available for a Senior Data Scientist based in Pretoria.

**Requirements**:

- Bachelor’s or Honour’s degree in Statistics, Mathematics, Applied Mathematics, Physics, Econometrics, Actuarial Science or equivalent experience.
- Masters in Statistics, Mathematics, Applied Mathematics, Physics, Econometrics, would be advantageous.
- 6+ years’ experience in data science and analysis.
- Team management or leadership experience.
- Project Management experience.
- Proficient in Python, R, and database technologies.
- Valid driver’s license.
- Advanced working Python knowledge.
- Experience working with relational databases, query authoring Python as well as working familiarity with a variety of databases.
- Experience supporting and working with cross-functional teams in a dynamic environment.

KPAs:

- Support the chief digital officer and senior data architect using a variety of state-of-the-art cloud-based technologies to solve data analysis and prediction problems.
- Identify and act on new opportunities for data driven business in data science and analytics.
- Work in a collaborative environment developing data science methods, tools, and algorithms to solve problems.
- Become fluent in analytical modelling using the company’s internal data modelling platforms and tools.
- Cloud
- Big Data
- Machine Learning
- Business Intelligence or Analytics and visualisation.
- Languages such as: Python, R and SQL
- Load and merge data originating from diverse sources.
- Pre-process and Transform data for model building and analysis.
- Troubleshoot data quality issues and work with team members to reach solutions.
- Create visualizations to provide insights on large data sets and input to finished reports.
- Develop predictive models for business solutions.
- Deploy predictive and other models to production.
- Develop technical specification for 3rd party platform data integration and streaming.
- Participate in continuous improvement efforts to increase available data quality and delivery speed.
- Address ad-hoc domain-specific data analytic requirements from domain or cluster leaders.



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