Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Quantitative Analyst

Anson McCade
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst (CRM) - FTC

Data Analyst – Senior Consultant, Assistant Manager, Manager - Advisory Consulting

Senior Data Scientist

Senior Data Scientist - Environmental Sciences

Senior Risk Modelling Data Scientist

Graduate: Sustainability Data Analyst

 

My client trades LNG, gas, power and energy attributes - and connects independent producers, suppliers and corporate off-takers in the wholesale energy markets.

The Quantitative Analytics team is responsible for:

Providing high-quality model development that supports front office pricing and risk management of complex and structured products

Carrying out quantitative analysis of complex trading to help CET’s traders to maximise value and manage risk

Assisting originators in development of new products.

Job role:

The successful candidate will be required to:

Produce high quality increments to the team’s model library working both individually and collaboratively

Be able to assist/advise trading and origination via quantitative analysis and a strong mathematical/financial intuition

Develop within the team’s common Python code base.

The Person:

Masters Degree or PhD qualification within science, mathematics or other quantitative subject

Experience with derivatives pricing and risk management systems

Experience of having worked within a trading environment

Energy / commodity market familiarity

Experience of code development (including Python)

Strong Communicator

Strong interpersonal skills.

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.

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.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.