Job Summary

The Data Analyst is responsible for developing and implementing data-driven strategies to support the company’s business objectives. This includes analyzing large datasets to uncover trends, predict risks, and inform decisions related to pricing, underwriting, claims, and customer behavior, overall sections/business performance. The role ensures the company leverages its data assets to improve profitability, efficiency, and customer satisfaction.

Job Description

Accountability

• Assisting the departments/business in analyzing data and metrics to identify trends that are useful in decision making.
• Assisting in all phases of project work, including problem identification, formulation, model development, and deployment.
• Analyse source data and data flows, working with structured and unstructured data to determine trends and assist in better decision-making.
• Support in the development and enhancements of Macros in configuring data sets to specified or standard reporting templates for aggregation from multi systems.
• Build and maintain statistical models to forecast trends, assess risk, and optimize pricing and underwriting decisions. This may involve using techniques such as regression analysis, machine learning, and time-series forecasting.
• Analysing business performance and ensure alignment with the organization’s long-term vision and strategic objectives.
• Collaborate with departments like underwriting, claims, and sales to identify areas for improvement and implement data-driven solutions to enhance operational efficiency.
• Conduct comprehensive analysis of policy, claims, and sales data to provide actionable insights. Develop and maintain dashboards, reports, and data visualizations to track key performance indicators (KPIs) and present findings to senior management.
• Business Case Support: Contribute to the development of business cases for proposed projects.
• Manipulate high-volume, high-dimensionality data from varying sources to expose and highlight patterns, anomalies, relationships, and trends
• Apply AI and Machine Learning technology to solve complex, business problems
• Analyze and visualize diverse sources of data, interpret results in a business context, and report results clearly and concisely
• Communicate and present analytical models to the department management
• Work collaboratively with different business partners and be able to present results in a clear and concise manner.
• Design, develop, and implement state-of-the-art AI techniques; reproduce and apply existing algorithms/methods/models for financial applications.
• Innovate and advance AI techniques; evaluate and improve AI algorithms/methods/models currently used.
• Assist with developing and deploying AI educational workshops/seminar series for the staff to accelerate AI adoption.

​Accountability: People & Culture

• Fostering a corporate culture that promotes ethical practices and good corporate citizenship while maintaining a conducive work environment.
• Collaborate with cross-functional teams to develop initiatives that promote a positive and inclusive company culture.
• Individualized Development Planning: Create personalized development plans that align with your career aspirations and the organization’s objectives.

Accountability : Risk Management

• Compliance: Stay updated with insurance regulations and best practices to ensure compliance with industry standards
• Adherence to the laws and regulations of Kenya, the policies and regulations within the insurance industry and all internal company policies and procedures.
• Ensuring compliance with applicable statutory and regulatory requirements and establishing mitigation measures against emerging business risks.
• Drive a culture of proactive compliance in the function.

Education and Qualifications Required (Essential)

• Bachelor’s degree in Computer Science, Data Science, Engineering, Actuarial, Statistics, Economics, Mathematics, Business or other relevant qualifications.
• Diploma in Insurance/relevant Insurance professional Qualification will be an added advantage.
• Analytical Skills
• Machine Learning (ML)
• Artificial Intelligence (AI)
• Scalable Computing.
• 2-3 years relevant experience
• Have experience in operating in complex business environments and/or regulated sectors and have the personal qualities to develop strong stakeholder relationships

Technical skills

• Programming Languages: Proficiency in Python or R for data manipulation, statistical analysis, and modeling.
• Database Management: Strong skills in SQL for querying and managing large datasets.
• Business Intelligence Tools: Experience with data visualization and dashboard tools.
• Statistical Software: Familiarity with statistical software (e.g., SAS, SPSS).