I am an insurance data and operations professional with 15 years of experience spanning underwriting, claims, risk analysis, compliance, and operations management. I hold a Bachelor of Science in Actuarial Science and use analytical methods to improve decision-making, service delivery, and risk controls.
I work with SQL, Python, R, Tableau, and advanced Excel to clean, validate, analyze, and visualize data. My work includes claims trend analysis, frequency and severity modelling, loss reserving, KPI reporting, predictive analysis, financial modelling, and dashboard development.
In my operations leadership role, I oversee medical insurance schemes serving more than 4,500 principals and 20,500 beneficiaries while leading an 11-person team. I have streamlined workflows to achieve 95% SLA compliance, reduce processing time by 30%, and improve productivity by 20%.
I have strong experience in claims analytics, underwriting support, public liability claims, fraud and validity investigations, pricing support, and risk exposure monitoring. I have also reduced claim disputes by 25% through stronger verification controls, issue resolution, and process improvements.
I am experienced in insurance compliance, including IRA and AML-CFT requirements, SOP development, management reporting, root-cause analysis, vendor negotiation, and CRM and claims automation initiatives. My work has contributed to zero IRA non-compliance and approximately KES 2.5 million in annual vendor savings.
Since January 2026, I have also worked as a freelance AI trainer and evaluator for US-based AI companies. I evaluate and rank LLM outputs, write and review prompts, assess training data quality, and test models for factual accuracy, domain validity, and bias.
I work as an independent contractor on LLM training and evaluation projects for US-based AI companies. I support trainer and reviewer activities across AI quality-assurance workflows.
I write and review prompts and model responses, evaluate and rank AI outputs against detailed quality guidelines, and test models for factual inaccuracies, bias, and domain validity.
I oversee operations for two medical schemes serving more than 4,500 principals and 20,500 beneficiaries, while leading an 11-person team. I streamlined workflows to achieve 95% SLA compliance and reduce processing time by 30% while meeting IRA and AML-CFT requirements.
I reduced claim disputes by 25% through stronger controls, verification, and issue resolution. I use KPI analysis covering error rates, turnaround time, and satisfaction to produce monthly management reports, and led CRM integration and claims automation initiatives.
I trained staff on AML-CFT verification, contributing to a 20% productivity gain and zero IRA non-compliance in FY 2023/24. I also negotiated with vendors to deliver approximately KES 2.5 million in annual savings.
I analyzed market trends and customer insights to identify business opportunities and support coverage recommendations.
I applied actuarial and analytical techniques to support premium pricing and insurance product decisions.
I analyzed claims frequency, severity, and loss trends to support reserving decisions and loss projections.
I supported claims automation initiatives that reduced turnaround time by 20% and improved claims data reporting to reduce processing errors.
I processed high-volume insurance claims and investigated claim validity, coverage, and potential fraud in collaboration with underwriting and legal teams.
I reconciled broker and agent accounts, posted debits, followed up on late payments, and reported potential debtor issues to management.
I prepared policy documents and endorsements and supported the underwriting of new insurance risks.
Bachelor of Science, Actuarial Science
Google Data Analytics Professional Certificate, Data Analytics
Certificate of Proficiency in Insurance (COP), Insurance
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