• Start date: ASAP
• Duration: 12 months
• Location: 1 week on site, Dublin - 3 weeks working from home
• Rate: €200- €250 per day
Description:
- Bachelor’s Degree in a related field or equivalent practical experience
- Experience 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 internships
- Experience with reference data, data management, and data analytics
- Working 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 beneficial
- Interest in or exposure to advanced analytics, anomaly detection, or AI-driven data solutions is an advantage
The 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 Bring
- A proactive and curious mindset, with the ability to work both independently and collaboratively
- Strong investigative and analytical skills, with the ability to quickly understand complex issues and identify patterns or anomalies in data
- An interest in innovation and continuous process improvement
- Clear written and verbal communication skills, particularly when explaining complex topics
- Strong interpersonal skills and the ability to build effective relationships with business partners
- The ability to manage priorities and deliver against both short-term deadlines and longer-term objectives
The Value You Deliver
- Deliver high-quality, accurate, and timely data analysis and insights
- Identify and implement process improvements to enhance efficiency and data quality
- Provide root cause analysis and insights into data challenges, including identifying anomalies and trends
- Collaborate with business and technology partners to resolve issues and improve processes
- Support the adoption of automation and AI-driven approaches to strengthen data management
- Proactively contribute to and support a range of projects and initiatives
