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

Apply Now

Market & Data Analyst

Market Financial Solutions
Farringdon
1 year ago
Applications closed

Related Jobs

View all jobs

Investment Data Analyst

Data Analyst, London, United Kingdom

Alpha Data Services – Data Analyst, Assistant Vice President

Alpha Data Services, Performance Ready Data Analyst, EMEA Lead, Vice President

Data Scientist - Hedge Fund

Data Scientist - Hedge Fund

Market Financial Solutions (MFS) is a leading independent bridging finance provider based in the United Kingdom. With a strong presence in the market, we specialise in offering fast and flexible bridging loans and buy-to-let mortgages to our valued intermediaries and clients. Role Purpose: The purpose of the Market & Data Analyst role is to design, develop and maintain business intelligence solutions using Microsoft Power BI. The ideal candidate will have a strong analytical mindset, proficiency in data visualisation, and experience in handling large datasets. We are looking for an Excel and Power B.I. allrounder to obtain and model data into actionable insights to make real change. In addition, they will work with our main funder analyst team to exchange data, work with third parties to accurately represent our products, and have the drive to develop data warehouses to provide regular MI. Key Responsibilities: Develop, publish, and schedule interactive Power BI reports and dashboards based on business requirements. Document processes, models, designs, and solutions, and ensure availability of these documents to all relevant stakeholders Identify weaknesses, risks, and opportunities, and present data-driven recommendations to management to support business cases. Work closely with Compliance and Funding teams to ensure we adhere and report on funding line eligibility, loan book attributes, underwriting pipeline, and loan concentrations. Maintain forecasts vs actuals for a wide variety of metrics and budgetary purposes. Deliver tasks to aid in the introduction of IT systems to benefit both BTL and Bridging, introducing efficiencies, scale capability, better data, and better customer/broker journeys. Monitor conversion of enquiries and speed of processing, to uncover actionable insights for improvement. Analyse competitor products, investor reports, property company data (e.g. house prices), and Bank of England data to provide insights that aid MFS management and decision-making. Role Requirements: Strong interpersonal and communication, both written and verbal, skills, and the ability to build and maintain relationships. Knowledge of data modelling, cleansing and analysis techniques. Ability to produce graphical representations and data visualisations. Advantageous: Negotiation skills, Financial and accounting analysis, Hubspot CRM, and specialist mortgage market (buy to let and bridging). Proficiency in Power BI, including DAX (Data Analysis Expressions) and M language is preferred. Experience with SQL and relational databases (e.g., SQL Server, Oracle). Strong understanding of data warehousing concepts, ETL processes, and data modelling. Why Work for us? Annual salary review & regular appraisals Bonuses and Incentives Enhanced Maternity and Paternity Leave Package Private Medical Health Care with Vitality Life Insurance Coverage Engaging Work Networking and Team Building Event Next Steps: Ready for an exciting career move? Hit ‘apply’ to express your interest, and if your CV aligns with our requirements, expect a call from one of our team soon to discuss this fantastic opportunity further

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.