Graduate Technical Writer

Quant Capital
London
4 weeks ago
Applications closed

Related Jobs

View all jobs

Data Analyst - Graduate

Graduate Actuarial Analyst (Machine Learning)

Graduate Machine Learning Engineer - Edinburgh - £30k

Technical Intern

Technical Intern

Technical Intern

Graduate Technical Writer

£35,000 Plus 10% Bonus

1 Day a week in West London Office


Quant Capital is urgently looking for a Technical Writer to join our high profile client.


My Client is a well known global (yet not too corporate) financial software (fintech) business that has developed a unique proprietary front office lending solution.


This role is with an exciting business in the consumer lending space. They have grown significantly over the past few years and are looking to add a motivated and experienced individual to join their growing data team. This role offers the chance to work end-to-end across a range of credit models in the business and take on a challenging role which will give you excellent exposure and experience in the credit modelling space.


Key responsibilities of a document writer data role:

  • Gathering information:

Interviewing subject matter experts, reviewing technical specifications, and analysing data to understand system functionalities and features.

  • Writing content:

Creating user guides, API documentation, data dictionary definitions, training manuals, white papers, and other technical documents.

  • Editing and revising:

Ensuring accuracy, clarity, and consistency in writing by proofreading and revising documents based on feedback.

  • Formatting and design:

Organizing information in a logical structure with appropriate visuals (diagrams, tables) to enhance understanding.

  • Collaboration:

Working with development teams, project managers, and quality assurance personnel to gather necessary information and ensure documentation aligns with project goals.


The Technical Writer should have:

  • Technical knowledge:Understanding of database concepts, data structures, programming languages, and relevant data analysis tools.
  • SQL and a basic understanding of financial modelling
  • Strong writing skills:Ability to convey complex technical information in a clear, concise, and engaging manner.
  • Attention to detail:Ensuring accuracy and consistency in technical documentation.
  • Organizational skills:Managing multiple documentation projects with deadlines
  • Communication skills:Effectively communicating with technical and non-technical audiences to gather information and explain technical concepts.



The environment is that of Facebook or Google, relaxed open with time to think and make the right decisions. The atmosphere is calm and relaxed with an open dress code. This is a role for techies, those who are motivated by the sharp end of technology and the possibility of making serious money doing something you are passionate about.



The Culture of the firm is startup esc with a flat team structure and a great group of guys who all enjoy themselves.


My client is based in West London 1 day per week in the office maximum

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 AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

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

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.