Capital Markets Data Analyst

YouLend
London
3 months ago
Applications closed

Related Jobs

View all jobs

HR Data Analyst

Gen AI Specialist

Manager Data Engineer - D&ET - Technology Consulting - Belfast & Derry/Londonderry

Senior Data Scientist

Co-Founder / CTO Opportunity – AI Tech Recruitment Start-Up

Co-Founder / CTO Opportunity – AI Tech Recruitment Start-Up

About Us

YouLend is the preferred global embedded financing platform for many of the world’s leading e-commerce sites, tech companies and payment services providers such as Amazon, eBay, Shopify, Mollie, Dojo, Paysafe, Just Eat Takeaway and Takepayments. Our software platform and APIs enable our partners to offer flexible financing products, in their desired branding, to their merchant base. With YouLend's AI-driven credit risk assessment solutions, more merchants and SMEs than ever can receive fast, flexible and affordable funding. We operate in 9+ geographies across the UK, EU and the US.

We believe that the future of financial services will be delivered by customer-oriented tech companies that embed financing in their customer journeys, and we are building the solutions that will power that future.

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.

Requirements

  • Develop and shape key metrics that drive insights into YouLend’s capital mandate portfolios and influence strategic decisions
  • Create impactful dashboards using cutting-edge visualization tools to automate and streamline asset monitoring for internal and external stakeholders
  • Collaborate with data-engineering teams to design and build database structures, empowering seamless automation and efficiency
  • Uncover trends in behaviour, enhancing cash flow modelling and forecasting to support YouLend’s ABS transactions and drive innovation in financial solutions
  • Actively participate in provide support through due-diligence processes during capital-raise events

Essential Skills:

  • 2+ years of experience in data analytics, preferably within the Finance/Fintech/ABS 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:

  • Financial Transaction experience
  • Strong problem-solving skills
  • Detail oriented, outcome and process focused
  • You are independent, ambitious, and self-motivated and looking to make an impact

Benefits

Why join YouLend?

  • Award-Winning Workplace: YouLend has been recognised as one of the “Best Places to Work 2024” by the Sunday Times for being a supportive, diverse, and rewarding workplace.
  • Award-Winning Fintech: YouLend has been recognised as a “Top 250 Fintech Worldwide” company by CNBC.

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 / Squash Club

 

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.

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.