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

Apply Now

Junior Quants with Superb C++ Skills / $120 + Bonus

Eka Finance
London
8 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Quant Engineer - Investment banking/ XVA

Junior Data Analyst

Junior Customer Data Analyst

Junior Data Analyst Apprentice

Junior Data Analyst

Junior Data Scientist

Junior Quants with Superb C++ Skills / $120 + Bonus

You will be responsible for projects from initial idea generation through to implementation and execution, tackling challenges in areas such as prediction, optimisation, and data analysis.

Your research will involve large and often complex data sets. Your tools will be a range of computer programming languages (such as C++ and Python) and analysis packages, and their in-house development infrastructure.

Requirements:

  1. You must have an advanced degree in mathematics, computer science, physics, statistics, or econometrics.
  2. Proven research ability is desirable, together with strong programming skills.
  3. You will be confident using statistics as a tool to validate experimental results.
  4. You must be very comfortable coding in C++ or Python. Any experience with C++, Python, Big Data / Scientific computing experience will be desired.
  5. Please do not apply if you do not have extremely strong C++ coding skills.

Apply:

Please send a PDF format resume to

Job Overview

ID: 1368654

Date Posted: Posted 2 days ago

Expiration Date: 15/04/2025

Location: London

Competitive

#J-18808-Ljbffr

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.