Consultant

d-fine
London
1 year ago
Applications closed

Related Jobs

View all jobs

Consultant - Manager, Data Science and Machine Learning, AI & Data, Defence & Security

Consultant - Manager, Data Science and Machine Learning, AI & Data, Defence & Security

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

Consultant - Manager, Data Science and Machine Learning, AI & Data, Defence & Security

Consultant Data Analyst

Energy & Water Data Analyst

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.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

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.