Jubilee Insurance was established in August 1937, as the first locally incorporated Insurance Company based in Mombasa in 1937. Jubilee Insurance has spread its sphere of influence throughout the region to become the largest Composite insurer in East Africa, handling Life, Pensions, general and Medical insurance.

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Forensic Investigation & Data Analytics Intern

Job Type

Contract

Qualification

BA/BSc/HND

Experience

Location

Nairobi

Job Field

Data, Business Analysis and AI , Graduate Jobs , ICT / Computer

Job Ref. No: JLIL 384

Role Purpose

The Forensic Investigation & Data Analytics Intern will be responsible for supporting the execution of forensic investigations into suspected fraud, misconduct, and unethical behaviour across the business, while applying advanced data analytics techniques to strengthen investigative outcomes. The role combines structured investigative exposure with in-depth data interrogation, anomaly detection, and fraud trend analysis to support evidence development, loss quantification, and control improvement. The role holder will work within the Forensics & Security Services Department to enhance both investigative effectiveness and data-driven fraud detection, while upholding the highest standards of integrity, confidentiality, and professionalism.

Key Responsibilities

Strategy

• Support the implementation of fraud risk management initiatives through both investigative input and data-driven insights.
• Analyse fraud trends, patterns, and emerging risk indicators using structured datasets to inform preventive and detective controls.
• Contribute to the development and refinement of fraud analytics dashboards, scripts, and monitoring tools.
• Provide analytical support to strengthen early detection mechanisms and continuous fraud monitoring efforts.

Operational

• Support the planning and execution of forensic investigations into suspected fraud, misconduct, or unethical behaviour.
• Extract, structure, and analyse large datasets from internal systems to identify anomalies, suspicious transactions, and behavioural patterns.
• Apply advanced analytical techniques (trend analysis, outlier detection, pattern recognition, reconciliation modelling) to support investigative findings.
• Assist in the collection, organisation, and preservation of physical and digital evidence in line with approved forensic methodologies.
• Prepare structured working papers, analytical summaries, and draft investigation reports for review by senior team members.
• Support loss quantification exercises using data modelling and reconciliation techniques.
• Maintain and update the case management system and investigation trackers with both case data and analytical outputs.
• Support the review and analysis of CCTV footage, access control logs, and other security system outputs where required.
• Assist in coordinating data requests and documentation required for internal stakeholders, auditors, or external investigators.
• Contribute to identifying control weaknesses and systemic gaps through combined investigative findings and data analytics insights.

Corporate Governance

• Support compliance with internal policies, legal requirements, and regulatory standards during investigations and data handling.
• Ensure evidence handling and analytical processes meet confidentiality and governance standards.
• Assist in preparing structured fraud trend reports and analytical summaries for management reporting.
• Uphold professional standards and ethical conduct in handling sensitive investigative and financial information.

People and Culture

• Support fraud awareness initiatives through preparation of data-backed insights and case learnings.
• Promote a culture of integrity, accountability, and ethical conduct.
• Collaborate effectively with internal stakeholders to support investigative and analytical objectives.
• Demonstrate continuous learning in forensic investigation techniques, fraud analytics tools, and data interrogation methodologies.

Key Competencies

1. Integrity and confidentiality.
2. Strong analytical and critical thinking ability.
3. Professional scepticism and investigative curiosity.
4. Problem-solving orientation.
5. Effective communication skills.
6. Time management and ability to meet deadlines.
7. Collaboration and stakeholder engagement capability.
8. Adaptability and willingness to learn.

Functional Skills

• Strong data analytics capability including proficiency in Excel (advanced), Power BI, SQL, Python, or similar analytical tools.
• Ability to extract, clean, transform, and analyse structured datasets.
• Understanding of fraud detection methodologies and investigative processes.
• Strong report writing and structured documentation skills.
• Analytical modelling and reconciliation skills for loss quantification.
• High attention to detail and accuracy.
• Ability to handle sensitive information with discretion and professionalism.

Key Deliverables for the Role

• Structured analytical outputs supporting active investigations.
• High-quality working papers and well-maintained case documentation.
• Timely draft investigation summaries integrating data-driven findings.
• Updated fraud analytics trackers and dashboards where applicable.
• Accurate anomaly detection reports highlighting emerging fraud risks.
• Effective support to ongoing forensic investigations and security operations.

Academic Qualifications

• Bachelor’s degree in Data Analytics, Statistics, Computer Science, Criminology, Forensic Science, or a related field with strong quantitative components.
• Relevant data analytics certifications (e.g., Power BI, Google Data Analytics, IBM Data Analyst, Tableau, SQL/Python analytics).
• Demonstrated coursework or projects in data analytics, statistics, forensic accounting, or investigative analysis.
• Professional certification such as CFE (in progress or interest demonstrated) is an added advantage.

Relevant Experience

• Demonstrated strong analytical capability through academic research, structured data projects, forensic case studies, audit analytics, or internship/attachment programmes involving data interrogation and investigative analysis.
• Exposure to fraud, audit, investigation, risk, or security-related coursework or projects is an added advantage.

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• Support the implementation of fraud risk management initiatives through both investigative input and data-driven insights.
• Analyse fraud trends, patterns, and emerging risk indicators using structured datasets to inform preventive and detective controls.
• Contribute to the development and refinement of fraud analytics dashboards, scripts, and monitoring tools.
• Provide analytical support to strengthen early detection mechanisms and continuous fraud monitoring efforts.
• Support the planning and execution of forensic investigations into suspected fraud, misconduct, or unethical behaviour.
• Extract, structure, and analyse large datasets from internal systems to identify anomalies, suspicious transactions, and behavioural patterns.
• Apply advanced analytical techniques (trend analysis, outlier detection, pattern recognition, reconciliation modelling) to support investigative findings.
• Assist in the collection, organisation, and preservation of physical and digital evidence in line with approved forensic methodologies.
• Prepare structured working papers, analytical summaries, and draft investigation reports for review by senior team members.
• Support loss quantification exercises using data modelling and reconciliation techniques.
• Maintain and update the case management system and investigation trackers with both case data and analytical outputs.
• Support the review and analysis of CCTV footage, access control logs, and other security system outputs where required.
• Assist in coordinating data requests and documentation required for internal stakeholders, auditors, or external investigators.
• Contribute to identifying control weaknesses and systemic gaps through combined investigative findings and data analytics insights.
• Support compliance with internal policies, legal requirements, and regulatory standards during investigations and data handling.
• Ensure evidence handling and analytical processes meet confidentiality and governance standards.
• Assist in preparing structured fraud trend reports and analytical summaries for management reporting.
• Uphold professional standards and ethical conduct in handling sensitive investigative and financial information.
• Support fraud awareness initiatives through preparation of data-backed insights and case learnings.
• Promote a culture of integrity, accountability, and ethical conduct.
• Collaborate effectively with internal stakeholders to support investigative and analytical objectives.
• Demonstrate continuous learning in forensic investigation techniques, fraud analytics tools, and data interrogation methodologies.

• Strong data analytics capability including proficiency in Excel (advanced), Power BI, SQL, Python, or similar analytical tools.
• Ability to extract, clean, transform, and analyse structured datasets.
• Understanding of fraud detection methodologies and investigative processes.
• Strong report writing and structured documentation skills.
• Analytical modelling and reconciliation skills for loss quantification.
• High attention to detail and accuracy.
• Ability to handle sensitive information with discretion and professionalism.
• Integrity and confidentiality.
• Strong analytical and critical thinking ability.
• Professional scepticism and investigative curiosity.
• Problem-solving orientation.
• Effective communication skills.
• Time management and ability to meet deadlines.
• Collaboration and stakeholder engagement capability.
• Adaptability and willingness to learn.

• Bachelor’s degree in Data Analytics, Statistics, Computer Science, Criminology, Forensic Science, or a related field with strong quantitative components.
• Relevant data analytics certifications (e.g., Power BI, Google Data Analytics, IBM Data Analyst, Tableau, SQL/Python analytics).
• Demonstrated coursework or projects in data analytics, statistics, forensic accounting, or investigative analysis.
• Professional certification such as CFE (in progress or interest demonstrated) is an added advantage.
• Demonstrated strong analytical capability through academic research, structured data projects, forensic case studies, audit analytics, or internship/attachment programmes involving data interrogation and investigative analysis.
• Exposure to fraud, audit, investigation, risk, or security-related coursework or projects is an added advantage.