German Speaking Team Lead - Credit Analyst

London
9 months ago
Applications closed

Related Jobs

View all jobs

Experienced Recruitment Consultant – Artificial Intelligence

Senior Climate Data Scientist

Computer Vision and Artificial Intelligence Engineer

A thrilling opportunity has arisen for a German-speaking Team Lead Credit Analyst to join an innovative fintech company, either at their Frankfurt office, their new Berlin location, or their London headquarters! This is a permanent full-time role, to work on a hybrid scheme 2 days per week from the office based in the city centre.

Your Key Responsibilities:

Leading, developing, and training a team of credit analysts.
Providing structured feedback to enhance team performance.
Supporting complex credit decisions and optimizing processes with data science teams.
Using data-driven insights to assess loan applications efficiently.About You:

The ideal candidate is a strategic leader with strong analytical skills and a passion for empowering teams. With experience in credit analysis, lending, or underwriting, you thrive in a fast-paced environment and have a deep understanding of risk and revenue factors in SME financing. You'll be joining a dynamic, diverse team with opportunities for career growth, training, and unique perks such as company Summer and Winter trips, employee stock ownership program, a sabbatical after 4 years, and more!

Profile:

High Fluency in German and English to business standards (written and spoken).
Minimum 2 years of experience leading an operational team.
At least 4 years of experience in credit analysis, lending, or underwriting (SME sector preferred).
Strong expertise in financial statement analysis.
Excellent communication, leadership, and decision-making skills.
A proactive, solution-driven mindset with a keen eye for process improvements.To apply, please send your CV in English and in Word format to Alexia.
languagematters is acting as an employment agency in relation to this vacancy

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.