Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Market Data Analyst

S4 Market Data
London
9 months ago
Applications closed

Related Jobs

View all jobs

Market Data Analyst

Capital Market Data Analyst

Senior Data Analyst Technology (Product, Engineering, Design) · London ·

Investment Data Analyst

Data Analyst, London, United Kingdom

Graduate Data Analyst, London, United Kingdom

Summary:PLEASE NOTE - This is NOT a technical role for a Data Analyst, Data Scientist or someone with an IT background. Candidates MUST have experience in the Market Data realm and be able to administer Market Data contracts. Please read the description before you applyThe Market Data Analyst at S4 Market Data will oversee client projects and be responsible for the overall service delivery of our managed services with respective clients. This position will manage market data service inquiries and projects from clients as well as manage a market data administrator within the projects to ensure administrative tasks are being completed in an accurate and timely manner. The ideal candidate will have market data vendor management and administrative experience; sourcing and negotiating contracts, managing procurement/sourcing requests throughout the spend life cycle, speaking with internal business units and stakeholders (legal, finance, IT, etc.) to procure goods/services for our clients.  The candidate needs to be located in the US, this is a fully remote position. Responsibilities: Handle day-to-day demand management or vendor management and administrative inquiries from internal business units, including but not limited to; data/sourcing requests, contract negotiation, entitlement administration, exchange reporting, moves/adds/changes requests, inventory management, procurement/legal approval, expense allocation, invoices reconciliation, and spend reporting. Interact with the client’s various internal stakeholders and business units; technology, legal, accounting/finance, human resources, and investment managers. Oversee the inventory management process of leavers/joiners, ensure current inventory is accurate and up-to-date. Oversee the reconciliation invoices and validation of monthly allocations/expenses. Conduct monthly/quarterly exchange reporting and ensure exchange policies and data compliance across the client’s end-users and applications.  Administer their datafeeds (EMRS, DACS, Etc.) Review spend and enact cost savings and avoidance initiatives. Provide respective business units with an overview for their costs; understand their products/services and respond to any inquires as needed. Maintain reports on costs and identify ways to consolidate spend. Conducts regular internal team meetings to report on client SLA’s and to ensure all client service deliverables are being met and completed. Qualifications: Bachelor’s degree in MIS, Business, or related degree and 3-5 years of relevant experience in financial services or market data. Relevant work experience in consulting is preferred. Experience working with Market Data vendors such as Bloomberg, FactSet, Exchanges (NYSE, ICE, etc.). Knowledge of FITS and MDSL inventory systems is preferred. Excellent communication and project management skills and experience in working closely with internal client business units and senior stakeholders. An entrepreneurial and self-regulating mind-set. Display a high level of time management skills to manage multiple and elaborate requests simultaneously. Have high energy and be a self-starter with the ability to work independently and as part of a team. Powered by JazzHR

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.