To leverage advanced data analysis techniques, data science methodologies, and stakeholder engagement to understand business needs, identify risks, influence strategy, and manage costs in compliance with regulatory requirements.
Requirements
Qualifications
- Bachelors degree or equivalent qualification in a relevant field such as Business Analytics, Computer Science, Information Systems, Information Technology, or a related field (Essential)
- Master's degree or equivalent qualification in a relevant field such as Data Science, Statistics, Computer Science, Analytics, Applied Mathematics, or Business Analytics (Desirable)
- Advanced SQL Programming certification (Desirable)
- Python certification (Desirable)
- Analytical tools certification (e.g., PowerBI, QlikView, Cognos, Tableau) (Desirable)
- Understanding of business and data analytics practices, including knowledge of industry trends, best practices, and emerging technologies in data analysis and business intelligence.
- Understanding of data structures, data management principles, and data warehousing concepts, encompassing knowledge of relational databases, data modelling, ETL (Extract, Transform, Load) processes, and data integration techniques.
- Knowledge of SQL programming and database management, with expertise in writing efficient queries, optimising code, and ensuring data integrity.
- Statistical knowledge and expertise in applying statistical methods, hypothesis testing, and modelling techniques for data analysis and decision-making.
- Understanding of data visualisation principles and tools (e.g., tools Tableau, Power BI, or matplotlib).
- Familiarity with statistical tools and software for data analysis, such as Python libraries (NumPy, Pandas, scikit-learn) or R packages, to extract insights and perform advanced data modelling.
- Knowledge of data analysis techniques, including statistical analysis, data mining, and data modelling, to derive meaningful insights from complex datasets.
- Communication skills (written and verbal)
- Computer skills
- Report writing skills
- Data analysis skills
- Data management skills
- Data visualisation skills
- Problem solving skills
- Critical thinking skills
- Statistical data analysis skills
- Statistical modelling skills
- Programming skills (SQL)
- Programming skills (Python)
- A minimum of 5 years of relevant experience, in data analysis, data mining, and data modelling (essential)
- 2 years or more of experience in using data visualisation tools such as Power BI, QlikView, Cognos, or Tableau (essential)
- Experience with statistical analysis, hypothesis testing, and predictive modelling techniques (essential)
- Experience in data warehousing and a solid understanding of general business principles and operations (essential)
- Insurance/Finance industry (desirable)
PROCESS
- Conduct deep analysis of data patterns to identify actionable insights that support informed business decisions.
- Play a key role in shaping the business data infrastructure, including data warehousing, reporting, and analytics capabilities.
- Identify and resolve data gaps that impact the fulfilment of the business's functional requirements.
- Build and operationalise processes to ensure timely data-loading, accuracy, and relevance of data in the business intelligence warehouse.
- Leverage relevant business intelligence tools, effectively utilising their functionalities to enhance data analysis, visualisation, and reporting, thereby driving informed decision-making and maximising the value derived from data insights.
- Develop and design robust data structures that optimise self-service capabilities, enabling users to easily access, navigate, and derive insights from data, thereby enhancing the efficiency and effectiveness of self-help functionality within the organisation.
- Create visually compelling and intuitive solutions for data representation, enabling stakeholders to easily comprehend and interpret complex information.
- Produce precise and comprehensive documentation that effectively communicates project details, data models, and processes, supporting efficient collaboration and knowledge sharing.
- Optimise SQL code to minimise resource utilisation, ensuring efficient utilisation of space and hardware, and enhancing overall system performance.
- Utilise various tools to develop statistical models, diagnosing, validating, and iteratively improving their performance using SQL or other available methods, empowering data-driven decision-making.
- Perform thorough data analytics to detect and flag transactions that breach specified rules and thresholds, refining analyses to minimise false positives and accurately identify anomalies.
- Enhance existing data models by implementing improvements and incorporating best practices, driving operational efficiency and effectiveness in data processing and analysis.
- Continuously assess data requirements and develop automated reporting solutions to streamline data extraction, enabling efficient access to critical information and reducing manual effort.
- Ensure data quality in systems by actively debugging, testing, and documenting processes, identifying and rectifying issues to deliver optimal value to the business and ensure accurate decision-making.
- Lead and mentor a team of data analyst.
- Conduct high-level analyses of expenditure, drilling down to highlight high-risk providers for investigation and mitigation.
- Perform routine quality checks on data outputs to ensure robust, accurate, and reliable data for internal and external clients.
- Collaborate with business Head of Department (HOD), management, and key stakeholders to develop detailed business requirements, conduct gap analyses, and guide business leadership through analytical data.
- Deliver clear, engaging, unambiguous, and informative reports tailored to specific business requirements.
- Offer comprehensive support to the business, aligning with regulatory requirements, by developing and implementing compliance frameworks, conducting audits, and providing guidance and expertise to ensure adherence to relevant regulations and industry standards.
- Collaborate in developing key performance indicators (KPIs) within business units to proactively identify trends, measure progress, and evaluate the effectiveness of business initiatives.
- Construct logical and conceptual data flows that align with business unit requirements, facilitating the efficient and effective utilisation of data to drive informed decision-making and achieve strategic objectives.
- Propose and implement control improvement strategies, leveraging industry best practices and insights, to optimise operations and mitigate risks, and present recommendations to stakeholders for enhanced decision-making.
- Provide comprehensive support to all business operations and initiatives, fostering a culture of data-driven decision-making, improving data quality, and driving overall business performance.
- Gain a deep understanding of the business's functional and data requirements by actively collaborating across diverse business units, enabling alignment and delivery of tailored data solutions that meet specific organisational needs.
- Proactively support the business management team by delivering timely and insightful management information, leveraging data analysis and strategic insights to enable informed decision-making and drive business growth and success.
- Ensure the efficient and accurate execution of tasks by Junior Data Analysts, provide guidance and mentorship to support their professional growth, and maintain high-quality standards in data analysis processes.
- Collaborate with cross-functional teams, build relationships, and drive innovative solutions that align with business goals and objectives.
- Optimise SQL code composition to efficiently extract and transform data, enabling seamless delivery of insightful and actionable information to the management team, thereby facilitating informed decision-making.
- Identify and evaluate opportunities to optimise cost-effectiveness and enhance operational efficiency, implementing strategies and initiatives that drive financial savings and streamline processes for improved resource allocation.
- Demonstrate responsible management of financial and company resources, ensuring prudent utilisation and allocation while adhering to established policies and ethical considerations.
- Contribute valuable insights and input into the risk identification processes, actively participating in risk assessments, and effectively communicating recommendations to the appropriate forum for informed decision-making and risk mitigation.
