What will you do?
We are driven at Miway to quickly assess claims and limit payouts to valid claims to ensure good service and value for money to our clients.
This is a high-impact role focused on shaping and scaling fraud detection, investigations effectiveness, and claims optimisation capabilities within a dynamic and evolving environment.
The successful candidate will lead a team and take ownership of key analytics-driven initiatives across claims and fraud, ensuring that models, insights, and decision frameworks are effectively translated into operational processes that deliver measurable business value.
This role combines technical modelling, operational implementation, and strategic ownership. It is suited to an individual who can bridge the gap between analytical design and real-world application, while driving continuous improvement across the claims value chain.
What will make you successful in this role?
Qualifications and Experience
Bachelor's degree in Actuarial Science, Data Science, Statistics, Mathematics, or a related field.
Nearly or newly qualified actuary preferred; however, highly technical and experienced data science candidates will also be considered.
Minimum of 5 years' experience in short term insurance pricing or other predictive modelling within the financial services sector.
Prior experience in managing or leading a team is essential.
Experience in claims, fraud, or operational analytics is strongly preferred.
Demonstrated experience in both technical model development and business implementation.
Proven track record of delivering cross-functional, business-impacting initiatives.
Key Responsibilities
Team Leadership and Delivery
Lead, mentor, and provide technical oversight to a team of analysts.
Foster a high-performance culture focused on accountability, quality, and business impact.
Ensure consistent delivery of high-value initiatives aligned to business priorities.
Manage and align stakeholders across claims, investigations, and broader business units.
Fraud Detection and Investigations Performance
Lead initiatives to improve fraud detection and investigation effectiveness.
Enhance case selection, reduce false positives, and improve investigation conversion rates.
Ensure robust tracking and measurement of investigation outcomes and financial impact.
Work closely with operational teams to align analytical outputs with investigation capacity and priorities.
Claims Performance and Optimisation
Drive initiatives to improve claims cost management and operational efficiency.
Identify and address claims leakage and inefficiencies across the value chain.
Enhance initial claims estimation and performance monitoring frameworks.
Translate analytical insights into practical, actionable business improvements.
Embedding Analytics into Operations
Ensure models, rules, and decision frameworks are effectively embedded into operational environments.
Identify and close gaps between analytical design and execution.
Collaborate closely with technical and operational teams to drive adoption and usability of solutions.
Reporting, Insights and Decision Support
Develop and maintain reporting and monitoring frameworks across fraud and claims.
Build dashboards and automated reporting to support data-driven decision-making.
Provide clear, actionable insights on performance, risks, and opportunities.
Continuous Improvement and Innovation
Establish feedback loops to continuously refine models, rules, and processes.
Identify opportunities to enhance fraud detection strategies and claims optimisation approaches.
Drive iterative improvement in analytical and operational capabilities.
Stakeholder Engagement
Act as a key interface between analytics, claims, investigations, legal, and external stakeholders.
Influence and drive adoption of data-driven decision-making across the business.
Lead performance discussions and ensure alignment to key business objectives.
Key Skills and Attributes
Strong understanding of the financial services value chain end-to-end; experience in short-term insurance, particularly within Claims and Fraud, is advantageous.
Strong analytical and modelling capability (e.g. GLMs, predictive modelling), with the ability to apply these in real-world contexts.
Ability to operate across both technical and operational environments, bridging the gap between analytics and business execution.
Strong commercial acumen, with the ability to prioritise initiatives based on business value and impact.
Proven ability to define problems, design pragmatic solutions, and deliver measurable outcomes.
Advanced SQL and analytical capability, with strong proficiency in R (required) and Python advantageous.
Strong stakeholder management and influencing skills across multiple levels.
Excellent communication skills, with the ability to translate technical concepts into clear business insights.
High attention to detail and strong problem-solving ability.
Self-driven, accountable, and delivery-focused.
Comfortable operating in ambiguous environments and building scalable solutions from the ground up.
Technical Tools
SQL (SQL Server and/or Oracle) - required
R - required
Dashboarding and reporting tools - required
Python - advantageous
Experience working with production environments and/or IT implementation - advantageous