National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Data Analyst

Crisil
Newtownabbey
3 days ago
Create job alert

Role: Senior Data Analyst (Capital and RWA remediation)

Experience: 5+ years

Location: Belfast, London, NY # of positions: 2 to 4 Role Description:

The role will be part of a Markets Transformation Team responsible for ensuring the timely execution of technical data centric deliverables.

Primary Responsibilities:

  • Own the design and delivery of Services required to support Credit RWA calculations.
  • Use independent critical thinking and data analysis to decompose complex problems into simple deliverables.
  • Lead working groups with Business, Quant, Finance and Technology stakeholders to identify critical data elements and design a target operating model / architecture.
  • Translate requirements and target architectures into delivery milestones and agree deliverables and project plans with stakeholders.
  • Maintain a hands-on approach to project delivery, working on a daily basis with technical teams to ensure requirements are understood, correctly implemented and delivered to plan.
  • Manage internal and external dependencies across initiatives, including working closely with Business, Quant, Finance and Technology teams .
  • Identify challenges and proactively seek to resolve or escalate risks and issues in a timely and well-articulated manner to the projects by engaging relevant stakeholders.
  • Produce accurate and insightful project update materials and artifacts, tailoring to various forums and committees.
  • Build strong relationships, adopting a joined up approach, to support the execution of programs.

Key skills required:

  • Entrepreneurial mindset with ability to work unsupported to develop ideas and formalise delivery plans.
  • Experience working with large datasets / relational databases and using sql to analyse and manipulate data.
  • Demonstrable hands-on experience of designing effective target operating models and IT architectures to solve complex business problems.
  • Excellent oral and written communications skills with ability to engage, inform and persuade senior stakeholders through discussion, presentations and use of data.
  • Self-starting with the ability to multitask, prioritize and proactively seek out teams and individuals across the organisation to help unblock issues.
  • Organized, detail oriented, and able to track multiple workstreams / projects at once.
  • 5+ years relevant experience.

Keu skills preferred:

  • Experience working on cross-asset or Front Office analytics builds or experience working directly with the Business / Quant teams in single asset class deliveries.
  • Strong understanding of front to back trade lifecycle for derivative products
  • Trading or Business Management experience

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.

The Ultimate Assessment-Centre Survival Guide for Machine Learning Jobs in the UK

Assessment centres for machine learning positions in the UK are designed to reflect the complexity and collaboration required in real-world ML projects. From psychometric assessments and live model-building tasks to group data science challenges and behavioural interviews, recruiters evaluate your statistical understanding, coding skills, communication and teamwork. Whether you specialise in deep learning, reinforcement learning or NLP, this guide offers a step-by-step approach to excel at every stage and secure your next ML role.