Manager, Data Analyst - Top Tier Financial Firm

Key Responsibilities

• Perform exploratory and advanced data analysis to identify trends, patterns, and anomalies in customer behaviour, digital engagement, and agency performance.
• Apply advanced statistical techniques and predictive modelling to solve business challenges and generate forecasts (e.g. customer lifetime value, churn risk, cross-sell/up-sell opportunities, and loss ratio predictions).
• Design and develop insightful dashboards, reports, and visualisations using Power BI, Tableau, or similar tools.
• Create compelling presentations to clearly communicate insights and recommendations to stakeholders and senior leadership.
• Collaborate closely with business, agency, customer, and IT teams to understand analytical needs and deliver high-impact solutions.
• Act as a trusted advisor, challenging assumptions and influencing strategic decisions with data-driven insights.
• Support digital initiatives by analysing UX data, conversion funnels, and A/B test results to drive continuous improvement.

Qualifications & Experience

• 5-7 years of relevant experience as a Data Analyst, preferably in insurance or financial services.
• Experience in insurance agency or distribution reporting is a strong advantage.
• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• Strong proficiency in Python and SQL for data analysis and manipulation.
• Solid knowledge of statistical analysis techniques and predictive modelling.
• Hands-on experience with data visualisation tools (Power BI or Tableau).
• Good understanding of insurance domain metrics (loss ratio, combined ratio, premiums, claims frequency/severity, retention, acquisition cost, etc.).
• Excellent communication and presentation skills, with the ability to translate complex technical insights into clear business recommendations.
• Strong problem-solving mindset, attention to detail, and ability to thrive in a fast-paced environment.
• Proactive, collaborative, and self-motivated with a passion for driving innovation through data.