Johannesburg: Data Scientist

Key Responsibilities Data Engineering & Architecture – Design, build, and maintain robust data pipelines that ingest, transform, and store structured and unstructured data from multiple sources. – Design and implement scalable data platform architectures to support evolving business needs – Manage and optimise database infrastructure for scalability, focusing on query optimization, indexing strategies, high availability, and cost effectiveness. Data Analysis & Insights – Develop and maintain a deep technical mastery of the end-to-end data ecosystem – Deep-dive into raw datasets where required to ensure that data outputs are logically sound, rigorously tested, and provide an accurate reflection of business reality. – Translate complex data from multiple sources into meaningful insights that support business decision-making across all functions (sales, operations, credit, Finance, Legal). -Perform high level data analysis to identify trends, risks, and opportunities within lending and financial datasets. Data Processing and Governance – Implement data quality checks, monitoring, and performance tracking to ensure the accuracy, completeness, and reliability of datasets. – Maintain data catalogs and lineage documentation to ensure data is discoverable, governed, and compliant with privacy and compliance regulations. – Implement and maintain data security best practices and access controls. Reporting & Dashboards – Develop and maintain automated SQL-based cloud reporting solutions. – Build intuitive, insightful BI dashboards for internal stakeholders and clients. – Ensure reporting is accurate, timely, and aligned to business KPIs. AI Enablement – Support and contribute to AI-driven initiatives, including automation and intelligent decision support. – Collaborate with stakeholders to identify opportunities where AI can enhance operational efficiency or customer needs. User Experience – Support the development of front-end data interfaces that improve usability and value for internal users and customers. – Ensure outputs are accessible, visually clear, and user-centric. Collaboration & Continuous Improvement – Work closely with business, IT, credit, and product teams to gather requirements, validate solutions, and troubleshoot. – Take a solution-driven, pragmatic, and collaborative approach to problem solving. – Stay current with emerging data, analytics, and AI technologies and frameworks, and apply learnings practically. Minimum Requirements – Degree in Information Systems, Computer Science, Engineering, Data Science, or a related field. – Minimum 4 years experience in building end-to-end data solutions. – Proven experience within the financial services or lending sector. Strong proficiency in: o Advanced SQL – complex queries, stored procedures, and performance tuning o Data analysis, reporting, and BI Dashboard development o ETL/ELT Frameworks, automated workflows, or cloud-native orchestrators. Advantageous experience : o Azure cloud data platforms o BI & visualization tools o Modern data stacks and streaming services