Market Data Analyst

S4 Market Data
London
11 months ago
Applications closed

Related Jobs

View all jobs

Market Data & Reference Data Analyst (Contract)

Senior Market Data Analyst - Client & Ops Leader

Data Analyst

Senior Claims Data Analyst - NonVolume

Online Data Analyst - Punjabi (UK)

Senior Data Analyst

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.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Education Jobs

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Jobs

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

🍪 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.