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

Apply Now

Capital Market Data Analyst

YouLend
City of London
2 days ago
Create job alert

YouLend is a rapidly growing FinTech that is the preferred embedded financing platform for many of the world's leading e-commerce platforms, tech companies, and Payment Service Providers. Our software platform enables our partners to extend their value proposition by offering flexible financing products in their own branding, to their merchant base, without capital at risk.

We are owned by the leading Private Equity company, EQT, and have grown +100% year-on-year since 2020. We are headquartered in London, UK, but are also present in several European countries as well as the United States where we service our partners, including eBay, Amazon, Just Eat, Shopify, and Stripe.

The Role

To meet the growing demand for our technology and services, we are now seeking Capital Markets Data Analyst to join our Finance/Capital Markets team. Being one of the fastest growing Fintech businesses globally we are looking for exceptionally talented and self-motivated individual who has a desire to build a career within the Company.

  • Automate and optimize portfolio monitoring by building dashboards using visualisation tools
  • Identify trends and communicate insights to the senior executives
  • Build database tables alongside data-engineering teams to enable automation
  • Assess and manage the performance of underlying capital mandates
  • Perform financial analysis and develop cashflow models to support capital allocation and portfolio decision-making

Requirements

  • 2+ years of experience in data analytics, preferably within the Finance/ Fintech sector
  • Strong academic background including at least a Bachelor's degree (Mathematics, Engineering, Statistics, Computational Finance) or equivalent
  • Strong hands-on experience with SQL, Python
  • Experience with data visualisation tools, e.g Tableau
  • Dbt (Data build tool) experience would be beneficial (but not required)
  • Exceptional communication skills to help deliver insights to diverse stakeholders

Desirable Skills

  • Detail oriented, outcome and process focused
  • You are independent, ambitious, and self-motivated
  • You are independent, ambitious, and self-motivated and looking to make an impact

Benefits

Why join YouLend? At YouLend, we champion diversity and embrace equal opportunity employment practices. Our hiring, transfer, and promotion decisions are exclusively based on qualifications, merit, and business requirements, free from any discrimination based on race, gender, age, disability, religion, nationality, or any other protected basis under applicable law.

We Offer Comprehensive Benefits Package That Includes

  • Stock Options
  • Private Medical insurance via Vitality
  • EAP with Health Assured
  • Enhanced Maternity and Paternity Leave
  • Modern and sophisticated office space in Central London
  • Free Gym in office building in Holborn
  • Subsidised Lunch via Feedr
  • Deliveroo Allowance if working late in office
  • Monthly in office Masseuse
  • Team and Company Socials
  • Football Power League / Padel League


#J-18808-Ljbffr

Related Jobs

View all jobs

Market Data Analyst

Data Analyst - Integrations

Executive Compensation Data Analyst

Senior Data Analyst

Private Credit Data Analyst

Senior Data Analyst

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.