Data Analyst

Opus Recruitment Solutions
London, UK
12 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Compensation
£67,600.0 - £75,400.0
Working hours
Regular working hours
Job source

Tech stack

Data Analysis Big Data Database Queries R (Programming Language) Python (Programming Language) Power BI SAS (Software) Tableau (Software) Transaction Data Data Analytics Performance Monitor Tools for Reporting

Job description

We are seeking two Data Analysts with experience within the Payments, Banking, FinTech, or Cards sector to support a range of analytical and reporting initiatives. This is an excellent opportunity to work on customer analytics, performance reporting, and dashboard automation within a fast-paced environment., * Conduct backbook segmentation and customer analytics.

  • Support propensity modelling and predictive analytics activities.
  • Deliver performance reporting and business insights.
  • Develop, automate, and maintain dashboards and MI reporting.
  • Analyse large datasets to identify trends and actionable recommendations.
  • Collaborate with stakeholders to translate business requirements into analytical solutions.
  • Ensure data accuracy and quality across all reporting outputs.

Requirements

  • Experience as a Data Analyst within Payments, Banking, FinTech, Cards, or Financial Services.
  • Strong SQL skills for data extraction and analysis.
  • Experience with Power BI, Tableau, or similar visualisation tools.
  • Knowledge of customer segmentation, reporting, and analytics.
  • Strong analytical and problem-solving capabilities.
  • Excellent communication and stakeholder management skills.

Desirable

  • Exposure to Python, R, SAS, or other analytics tools.
  • Experience with propensity modelling or predictive analytics.
  • Understanding of customer behaviour, transaction data, and payments products.

Benefits & conditions

  • 12-month contract with a leading organisation.
  • Opportunity to work on business-critical analytics projects.
  • Hybrid working model with London-based collaboration.
  • Suitable for ambitious analysts with relevant payments experience and strong technical skills.

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