Top Data & Analytics Jobs

Processes and validates managed investment data across global markets, ensuring accuracy, completeness, and timely delivery. Builds relationships with fund companies and internal teams, manages data issues, supports acquisition channels, and translates client requests into specifications and user stories. The role also improves procedures, documents use cases, develops analytical tools, and contributes to process improvement projects using methodologies such as Lean Six Sigma.

Owns Morningstar’s fund data activities in South Africa, serving as the primary liaison between centralized data teams and asset managers. Responsibilities include explaining data workflows, acquiring and onboarding complex datasets, supporting sales and client inquiries, coordinating global priorities, managing database enhancement projects, analyzing market and regulatory trends, engaging industry associations, and monitoring competitors. The role requires strong investment-industry knowledge, analytical and communication skills, and significant financial data experience.

Processes and validates managed investment data across global markets, ensuring accuracy, completeness, and timely delivery. Collaborates with global teams, fund companies, and internal clients; manages data issues, acquisition channels, specifications, and user stories. The role also improves procedures, develops analytical tools, documents use cases, and supports process improvement initiatives using Lean Six Sigma methodologies.

Research and analyze managed investment data, translating business methodologies into data, process, and technology solutions. Design data flows, interfaces, backend logic, and quality controls; conduct feasibility and impact analyses; document requirements; coordinate implementations; communicate risks; and support data-processing improvements across global teams.

Entry-level data and operations role supporting collection, verification, and maintenance of investment-related datasets. Respond to internal/client queries, follow research methods and policies, collaborate cross-functionally to resolve data issues, and learn Excel, SQL, and Power BI through structured training during a 6–12 month apprenticeship.

Build and launch benchmark, thematic, factor, strategic beta, and multi-asset indexes from concept through market launch. Conduct quantitative research, data analysis, signal testing, back-testing, portfolio construction, risk modeling, and statistical testing. Use Python and AI tools to automate workflows and accelerate methodology development. Create prototypes, dashboards, research materials, methodology documents, and client-facing narratives while partnering with research, product, technology, operations, and commercial teams.

Owns product quality frameworks and governance for ESG products across the product lifecycle. Defines quality standards, KPIs, dashboards, controls, and assurance plans; validates features, releases, and methodologies; monitors performance; leads root cause analysis and corrective actions; and drives automation, AI-enabled quality controls, process improvement, and cross-functional transformation with Product, Research, Technology, Data Operations, and Client Services.

Build and maintain enterprise data pipelines, ELT processes, data models, reporting structures, and analytics solutions. Cleanse, deduplicate, normalize, and govern data across warehouses and data lakes, including Snowflake. Develop dashboards and business intelligence models, ensure data quality and compliance, apply business logic, and collaborate with technical and non-technical stakeholders to deliver accurate insights and improve operational performance.

Design and build scalable data pipelines, APIs, and data services using cloud and open-source technologies. Ensure data quality, performance, and maintainability, collaborate with cross-functional teams, contribute to engineering best practices, and leverage AI-assisted tools to improve productivity.

Lead a team of Data Consultants across Australia & New Zealand to onboard and manage complex managed-investment datasets, build and escalate relationships with asset managers and third-party providers, provide data expertise to product and commercial teams, monitor market/competitor trends, collaborate with global stakeholders, and develop team capabilities to improve data quality and operational productivity.