Data Analyst
Role details
Job location
Tech stack
Requirements
Description:Bachelor's Degree in a related field or equivalent practical experienceExperience working as a Data Analyst (typically 1-2 years), ideally within financial services or a data-rich environment; we will also consider recent graduates with relevant skills or internshipsExperience with reference data, data management, and data analyticsWorking knowledge of tools and techniques for analysing and presenting data, such as SQL, Python/R, and Power BI (or similar tools)Familiarity with data vendor products (e.g., Bloomberg, Reuters) is beneficialInterest in or exposure to advanced analytics, anomaly detection, or AI-driven data solutions is an advantageThe Purpose of Your Role In this role, you will balance day-to-day data quality and production activities with analytical and project-based work, with a strong focus on quality and continuous improvement. You will also have the opportunity to contribute to the evolution of our data capabilities, including the use of automation, anomaly detection, and AI techniques to enhance data quality, efficiency, and insight generation. The Skills You BringA proactive and curious mindset, with the ability to work both independently and collaborativelyStrong investigative and analytical skills, with the ability to quickly understand complex issues and identify patterns or anomalies in dataAn interest in innovation and continuous process improvementClear written and verbal communication skills, particularly when explaining complex topicsStrong interpersonal skills and the ability to build effective relationships with business partnersThe ability to manage priorities and deliver against both short-term deadlines and longer-term objectivesThe Value You DeliverDeliver high-quality, accurate, and timely data analysis and insightsIdentify and implement process improvements to enhance efficiency and data qualityProvide root cause analysis and insights into data challenges, including identifying anomalies and trendsCollaborate with business and technology partners to resolve issues and improve processesSupport the adoption of automation and AI-driven approaches to strengthen data managementProactively contribute to and support a range of projects and initiatives