Data Science Professional in Training (PIT)
Trainee data scientist (Professional in Training) at a consulting studio in Durban: collects, cleans, and analyses client data, builds predictive ML models and dashboards, and helps develop data products and MVPs under senior guidance. Core stack: Python or R, SQL, Power BI/Tableau, Scikit-learn/TensorFlow, with exposure to AWS/Azure and emerging AI tools.
- Compensation
- Not disclosed
- Location
- Durban, South Africa
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data science
- Posted
Skills
Must have
- Degree/diploma in Data Science, Statistics, Mathematics, Computer Science, Information Systems, Engineering, Economics, or related quantitative field
- Familiarity with SQL and relational databases
- Familiarity with data analysis and visualisation tools such as Power BI, Tableau, or Python
- Understanding of statistical analysis, machine learning, and predictive modelling
Nice to have
- Experience with at least one programming language, preferably Python or R (advantageous)
- Exposure to cloud environments such as AWS or Microsoft Azure (advantageous)
- Understanding of data engineering, data governance, or MLOps practices (beneficial)
Full description
Brief job Description
The Data Science PIT supports the delivery of data-driven solutions that help clients solve complex business challenges and make better decisions. The role involves collecting, analysing, modelling, and interpreting data to generate actionable insights and develop innovative data science solutions.
Working closely with the senior team, the Data Science PIT will contribute to data exploration, statistical analysis, machine learning, visualisation, and the development of data products and minimal viable products (MVPs). The role provides hands-on exposure to consulting, data science, AI, cloud technologies, and emerging analytical tools within a dynamic and impact-driven environment.
This role is ideal for a curious, analytical, and self-motivated individual who enjoys solving problems with data, is passionate about technology and continuous learning, and is excited to apply data science to real-world business challenges.
Key Responsibilities
- Data Analysis & Insights
- Gain a clear understanding of client business challenges and identify how data can be used to address them.
- Collect, clean, transform, and prepare structured and unstructured data for analysis.
- Conduct exploratory data analysis to identify trends, patterns, relationships, and anomalies.
- Apply statistical and analytical techniques to generate meaningful business insights.
- Translate complex analytical findings into clear, actionable recommendations for clients and internal stakeholders.
- Support the development of reports, dashboards, presentations, and data-driven narratives.
- Data Science & Machine Learning
- Develop, test, and evaluate predictive and machine learning models to address business problems.
- Apply appropriate statistical, mathematical, and machine learning techniques to different use cases.
- Support model training, validation, optimisation, and performance monitoring.
- Work with machine learning frameworks and libraries such as Scikit-learn, TensorFlow, or similar tools.
- Identify opportunities to apply AI and advanced analytics to improve business processes and decision-making.
- Document methodologies, assumptions, results, and model limitations.
- Data Visualisation & Reporting
- Develop clear and intuitive data visualisations to communicate insights effectively.
- Build and maintain dashboards using tools such as Power BI, Tableau, or similar platforms.