Consultant

d-fine
London
1 year ago
Applications closed

Related Jobs

View all jobs

Consultant, Data Science and Business Analyst, AI & Data, Defence & Security

Senior Consultant - Data Scientist

Managing Consultant - C&M - Data Science

Data Engineering & Data Science Consultant

Data Engineering & Data Science Consultant

Artificial Intelligence (AI) Consultant

Consultant
from the fields of physics, mathematics, computer science, natural sciences, engineering or economics

Contract Period:permanent
Working Time:full-time
Location:London, everywhere in the UK and international
Entry Date:all year around (depending on availability)

d-fine is a continuously growing European consulting company with over 1, employees. Our London office in the heart of the City was established in to deliver services to our clients in the UK and Ireland. Our projects focus on quantitative challenges in software engineering, data analytics, financial risk management, data science, and the development of sustainable technological solutions. d-fine’s consulting approach is based on years of practical experience and dynamic teams with an analytical and technological focus.

Job description

Design of models, methods and processes in both the private and public sectors Software and data engineering, using agile methodologies and full-stack development Development and operationalisation of data-driven models Business analyses and simulations Design, implementation and validation of risk models Use of modern technologies such as machine learning or big data solutions Technical analysis and implementation of regulatory requirements Analysis, design and digitalisation of processes Selection, parameterisation and integration of systems

Requirements

Outstanding university degree (Master/PhD) in physics, mathematics, computer science or natural, engineering or economic sciences with a corresponding quantitative, analytical or technological specialisation English language proficiency Possess significant IT knowledge coupled with strong programming skills, including understanding of the underlying concepts Familiar with at least one of the following subjects: mathematical statistics, numerical analysis, simulation techniques (e.g. Monte Carlo), optimisation methods (e.g. simulated annealing), and financial mathematical modelling Motivated to work on challenging applied quantitative issues requiring both, business understanding and technological expertise Ability to work well in a team Ability to communicate effectively with peers as well as with senior employees of d-fine and our clients Work experience in trading, treasury or risk management may be an additional advantage

We offer

Interesting and varied projects across Europe A competitive salary The opportunity to work with highly talented and motivated colleagues The chance to work with a wide range of clients from specialized hedge funds and industrial conglomerates to banking institutions The option to extend your expertise of financial mathematics through participation in courses at leading international universities A wide range of additional benefits such as company pension scheme, private medical, remote working policy, company events and much more!

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.