Data Scientist

The Data Scientist role reports to the Analysis Team Lead within the Business Intelligence department. As a Data Scientist, you will design, develop, and maintain advanced analytical models that yield actionable insights. Your expertise will facilitate informed decision-making across departments, and you will communicate complex findings to stakeholders. This role involves internal collaboration with various departments and may include external interactions with third-party partners.

Duties and Responsibilities (include but not limited to):

1. Collaborate with stakeholders across all levels and business / technical areas to develop data-driven solutions, aligning business strategies with analytical insights.
2. Elicit business requirements, translating them into the appropriate data modeling, analysis and machine learning specifications.
3. Ensure high-quality data through profiling, validation, and verification (business relevance, accuracy, completeness, consistency, timeliness) for data intended for analytics and predictive modelling.
4. Design, build, deploy, and maintain advanced analytical models that are optimized for high performance, scale, reusability, ease of maintainability and auditability.
5. Analyze data to extract key insights, communicating findings through intuitive visualizations and recommendations to guide decision-making.
6. Train and support users in interpreting model outcomes and analysis results.
7. Take ownership of all tasks allocated to you, proactively communicating progress, status, blockers, risks, and issues.
8. Incorporate MLOps best practices in all model development (includes but not limited to version control, automated monitoring, data validation, automated integration and deployment).
9. Continuously upskill and stay abreast of new developments in the Data Analytics, Modelling, Machine learning and AI space tooling, methodologies, applications.
10. Engage with Source System custodians (Product Owners / Architects) to gain an understanding of the data collected, the architecture in which the data are stored and the process that produced it. In addition, provide corrective feedback to ensure that the availability, quality, and structure of the source system data can satisfy downstream analytics requirements.
11. Perform duties listed above using, but not limited to, the skills and experience outlined in the key requirements section below.

Key Requirements:

Education: Grade 12 or equivalent; quantitative field qualification (e.g., Mathematics, Statistics, Computer Science) or relevant experience.

Experience: 4+ years in analytical role; proficiency in reliable predictive model development and deployment (scalability, security, maintainability).

Skills:

1. Strong communication and presentation skills (technical and non-technical audiences).
2. Building Machine learning models (clustering, classification, regression and prediction).
3. Programming languages (Python, R or similar); SQL development and optimization.
4. Report / dashboard development and data visualization (Power BI, Tableau, Qlik).

Personal Attributes:

1. Team player
2. Strong organizational skills (prioritize and juggle tasks, stay focused under pressure)
3. Adaptable and growth-oriented mindset
4. High Agency / Execution-focused

Additional Skills / Experience:

Experience working in the Financial Services, Retail, Technology industries or high growth businesses. Experience working with cloud-based data analytics platforms, such as Snowflake, Azure, BigQuery or Redshift.