Manager, Data Analyst - Top Tier Financial Firm

We are looking for a Data Analyst who will be respsonsibl to drive a project that aims to establish a structured, data-driven framework to enhance governance, transparency, performance measurement, and decision-making across Interactive Agency engagements. This initiative is focused on building long-term analytical capability and sustainable performance management within the Interactive Agency ecosystem. The Supplier will provide a managed service to support Interactive.

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.

Desired Skills and Experience

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.