Data Scientist

11037 Citibank, N.A. United Kingdom
Belfast
1 week ago
Create job alert
Overview

The Data Scientist works as part of Markets FO CDE Triage team to help Markets manage changes to the FO CDE in line with regulatory interpretations and Model Governance. Responsible for supporting the review, prioritization and approval of all Front Office (FO) Critical Data Element (CDE) changes, including senior reporting and escalations.

Job Background/context

Within Counterparty Trading & Risk (CTR), the Markets Capital Advancement team drives and oversees execution and management of capital initiatives. The XVA trading desk (part of CTR) prices and manages risk of derivatives trades, including credit, funding and capital. The desks need Front Office staff focused specifically on capital for Markets. This role, within COO, will support the broader CTR team in ensuring FO CDEs are in compliance with enterprise-wide data policies.

Key Responsibilities
  • Deliver analytics initiatives to address business problems with the ability to determine data required, assess time & effort required and establish a project plan
  • Provide data analysis to FO CDE Triage team and other stakeholders
  • Drive improvements on underlying dataset: partner with MQA & IT to integrate into dataset Front Office/shadow version of RWA and other capital metrics across asset classes, and underlying sensitivities & attribution analysis
  • Review and compare FO version with official capital calculations, help with strategic system state
  • Impact the business directly by ensuring the quality of work provided by self and others; impacts own team and closely related work teams
  • Mines and analyzes data from various banking platforms to drive optimization and improve data quality
  • Deliver analytics initiatives to address business problems with the ability to determine data required, assess time & effort required and establish a project plan
Knowledge/Experience
  • Experience working with data analytics on large datasets, ideally within financial Markets
  • Proven ability analysing business needs, building visualisations, and tracking down complex data quality and integration issues
Skills
  • Very strong SQL and Tableau skills required. Python or other programming a plus
  • Strong analytical and mathematical skills
  • Attention to detail
  • Demonstrable team skills both within and across teams
  • Ability to pick up new concepts and think outside the box
  • Preferably comfortable with derivatives modelling concepts
Qualifications
  • Undergraduate numerate degree or higher
Job Family Group

Technology


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist (Government)

Data Scientist Placement

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.

Careers

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

Jobs

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

Education

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.