Funds Technology – Data Analyst Manager Assistant Manager Senior Consultant

Grant Thornton
Belfast
1 month ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst - Integrations

Data Engineering Manager (Data Platform)

Principal Reporting and Data Engineer

Systems and Data Analyst (Entry Level)

Senior Investment Data Analyst - Highly Prestigious Hedge Fund - London

Description


Join our fast-growing Technology Consulting team where you will work at the intersection of data strategy and financial services technology. As a Data Analyst specialising in Funds Technology you will collaborate with leading asset managers, fund administrators and institutional investors to unlock business value through smarter data use, system optimisation and digital innovation. This role blends business analysis, stakeholder engagement and hands‑on data expertise to shape how funds clients harness information for decision‑making and operational efficiency.


This is a client-facing consulting role designed for data professionals with strong business analyst capabilities and a desire to deliver change in a dynamic international environment. This hybrid role necessitates on‑site presence at client site as required by project or business needs.


Embrace the possibility to apply at Grant Thornton we are constantly upskilling our staff. If you do not meet all of the listed requirements please do not be discouraged from applying. We value a growth-oriented mindset and are dedicated to supporting you in reaching your full potential.


Roles & Responsibilities

Collaborate within a multi‑disciplinary team to successfully deliver and manage projects across a range of key areas including:


Funds Technology Analysis

  • Lead and support data‑driven projects across the investment lifecycle: from client onboarding and NAV oversight to investor reporting and regulatory compliance.
  • Elicit documents and translate complex business requirements into data and technology solutions.
  • Engage stakeholders across business and technology teams to deliver fit‑for‑purpose solutions aligned with strategic objectives.
  • Perform detailed data analysis, data quality assessment and reconciliation across systems and sources.
  • Design and improve operational processes through automation, analytics and system integration.
  • Contribute to the development of data governance frameworks, metadata management and control structures.
  • Prepare technical and business documentation including data dictionaries, workflow diagrams and business requirements documents.
  • Support client workshops, solution testing and deployment activities.

Business Development

  • Support and drive business development initiatives including the preparation of proposals and tenders for new client opportunities.
  • Work with colleagues to ensure data integrity and regulatory alignment in business development efforts.
  • Recommend improvements to data pipelines, dashboards and reporting tools to support business growth.

Skills and Experience


Education and Certifications

  • A third-level degree with a strong academic record in a quantitative field of study (e.g. Data Science, Statistics, Mathematics, Computer Science).
  • Minimum of 2–5 years of relevant experience in data analysis, business analysis or technology consulting within financial services, ideally funds or asset management.
  • Working knowledge of SQL or similar querying languages.

Required Experience: Manager


Key Skills

Databases, Data Analytics, Microsoft Access, SQL, Power BI, R, Tableau, Data Management, Data Mining, SAS, Data Analysis Skills, Analytics


Employment Type: Full-Time


Vacancy: 1


#J-18808-Ljbffr

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

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

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.