About the role
We are looking for a highly analytical Data Analyst with strong expertise in SQL, campaign management/campaign analytics, and banking (loans, mortgages, and deposits). The ideal candidate will work closely with business, marketing, and analytics teams to generate insights, optimise campaigns, and support strategic decision-making using data.
Responsibilities:
- Analyse large datasets using SQL to generate actionable business insights.
- Design, execute, and evaluate marketing/customer campaigns.
- Measure campaign performance and recommend optimisation strategies.
- Develop dashboards, reports, and KPIs for business stakeholders.
- Perform customer segmentation, campaign targeting, and performance analysis.
- Work with cross-functional teams, including Business, Marketing, Product, and Data Engineering.
- Identify trends, opportunities, and risks using analytical techniques.
- Ensure data quality, accuracy, and governance across reporting.
- Support business decisions related to customer acquisition, retention, and cross-sell initiatives.
- Present analytical findings to senior stakeholders in a clear and concise manner.
Requirements:
- 5-8 years of experience as a data analyst or campaign analyst.
- Hands-on experience working with banking datasets.
- Experience in campaign performance analysis and customer segmentation.
- Strong understanding of banking products such as loans, mortgages, and deposits.
- Experience working with large datasets and translating business problems into analytical solutions.
- Mandatory Skills: SQL (Advanced), Campaign Management / Campaign Analytics, Banking Domain, Loans / Mortgages / Deposits, Data Analysis, and Stakeholder Management.
Technical Skills:
- Strong SQL (Advanced Queries, Joins, CTEs, Window Functions, Performance Optimisation).
- Experience in data analysis and reporting, campaign analytics / campaign management, and Excel (advanced).
- Experience with BI tools such as Power BI, Tableau, or Looker (preferred).
- Domain Expertise: Banking and Financial Services, Loans, Mortgages, and Deposits.
Preferred Qualifications:
- Bachelor's degree in engineering, computer science, statistics, mathematics, economics, or a related quantitative field.
- Experience with Python or R is an added advantage.
- Knowledge of statistical analysis and A/B testing is preferred.
- Exposure to cloud platforms (AWS, Azure, or GCP) is a plus.
Key Competencies:
- Strong analytical and problem-solving skills.
- Excellent stakeholder management.
- Business acumen in retail banking.
- Effective communication and presentation skills.
- Ability to work in a fast-paced environment.
- Attention to detail and ownership mindset.