Senior Data Analyst

Job Description:

Role Summary

GAPM is establishing a small, cross-functional team to deliver artificial intelligence and digitalization capabilities on a Microsoft Azure platform. The Data Analyst is the bridge between technical delivery and the business: understanding what stakeholders require, shaping requirements, validating that data and artificial-intelligence outputs are correct and useful, and presenting results in a form that decision-makers can trust.

The post-holder is responsible for transforming complex data into actionable insights that support strategic decision-making. The role acts as a bridge between technical data teams and business stakeholders, ensuring data-driven improvements in performance, efficiency, and growth

Key Responsibilities

• Analyze large, complex datasets to identify trends, patterns, and business opportunities.

• Develop and maintain data models, dashboards, and automated reports to track performance metrics.

• Translate business questions into analytical frameworks and actionable insights.

• Collaborate with cross-functional teams (business, IT, data engineering) to deliver data solutions.

• Ensure data quality, integrity, and consistency across systems and reports.

• Present findings clearly to non-technical stakeholders and leadership.

• Lead or support advanced analytics initiatives (forecasting, experimentation, performance analysis).

• Mentor junior analysts and promote best practices within the team.

Skills and qualifications:

• Minimum 5 years of experience with SQL.
• Knowledge of statistical analysis and programming languages (Python preferred, R).
• Solid understanding of data modeling, ETL processes, and analytics frameworks.

• Strong problem-solving, strong analytical skills, and attention to detail.

• Experience performing exploratory data analysis on unfamiliar datasets, including profiling, identifying patterns and anomalies, and forming and testing hypotheses.

• Excellent communication skills for translating data into business insights.

• Proficiency with one data visualization tool, Power BI preferred.

• Demonstrable experience building reports, data models and calculations in Power BI to a professional standard.

• The ability to present data visually in a way that communicates the key message clearly.

Nice to have:

• A background in finance, insurance, or accounting, including an understanding of the associated data and reporting cycles.

• Familiarity with statistical techniques that support robust analysis.

• Familiarity with the behavior of artificial intelligence outputs, so that any assessment of them is informed rather than mechanical.

• Experience working alongside an engineering team in an iterative delivery setting.