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

Apply Now

Quantitative Researcher

AGITProp
Greater London
1 year ago
Applications closed

Related Jobs

View all jobs

Python Data Engineer - Hedgefund

Statistics & Data Science Innovation Hub Principal Data Scientist

Principal AI Research Scientist – Natural Language Processing

Research Scientist Intern, Monetization Computer Vision (PhD)

Research Scientist Intern, Monetization Computer Vision (PhD)...

Statistics & Data Science Innovation Hub Principal Data Scientist

Newly founded, AGITProp is an AI-driven quant research firm that is pushing the boundaries of algorithmic trading.


Quant firms have leveraged AI and ML for years, but the increasing complexity and scale of global markets demand a more comprehensive and integrated approach.


At AGITProp, we are leveraging the latest advances and insights from foundation and large language models (LLM) to build novel models across multiple modalities. We have ambitious growth plans and are searching for the best and brightest minds from across tech and finance to help us achieve our aim.


About the Role


We are seeking an experienced and highly skilled Senior Quant to join our team. In this role, you will be responsible for developing, implementing, and maintaining cutting-edge quantitative trading models, strategies, and algorithms. You will work closely with our trading, AI, and engineering teams to ensure the seamless integration of your quantitative models into our trading systems. The ideal candidate will possess a strong background in quantitative finance, statistics, and programming, with a demonstrated ability to develop and apply complex mathematical models to real-world financial market scenarios.


Responsibilities


  • Develop, implement, and maintain sophisticated quantitative trading models, strategies, and algorithms, ensuring their efficacy and alignment with the fund's objectives.
  • Collaborate with the trading and AI teams to integrate quantitative models into the trading system, identifying potential synergies and areas for improvement.
  • Perform rigorous backtesting and validation of quantitative models, ensuring their robustness, accuracy, and generalizability.
  • Analyze large and complex financial datasets, identifying patterns, trends, and market inefficiencies that can be exploited through quantitative strategies.
  • Continuously monitor and evaluate the performance of deployed quantitative models, making necessary adjustments and optimizations to maximize returns and minimize risk.
  • Stay current with the latest advancements in quantitative finance, machine learning, and relevant technologies, and proactively suggest improvements and innovations to the team's processes and tools.


Requirements


  • Master's or Ph.D. degree in Quantitative Finance, Financial Engineering, Applied Mathematics, Statistics, or a related field.
  • A minimum of five years of experience in quantitative finance or a related role, with a focus on developing and implementing quantitative trading models and strategies.
  • Strong proficiency in Python, R, or similar languages, with experience in relevant quantitative finance libraries and frameworks.
  • In-depth understanding of financial markets, instruments, and risk management principles, as well as the unique challenges and requirements associated with quantitative trading.
  • Excellent analytical, problem-solving, and statistical skills, with the ability to develop and apply complex mathematical models to real-world financial market scenarios.
  • Exceptional communication and collaboration skills, with the ability to work effectively in cross-functional teams.


We appreciate there isn’t a lot of information to go off from a company perspective. However, we can be very open about this and what we are looking to achieve throughout the screening and interview phase of the recruitment process.


At AGITProp, we believe the power of AI lies in its diversity, just like the teams who build it. We are committed to fostering a welcoming and inclusive environment where individuals from all backgrounds and experiences can thrive. We understand that a diverse workforce leads to richer perspectives, more innovative solutions, and ultimately, better results.


If this position is something that you are interested in, to apply, please submit your resume, brief cover letter, and any relevant publications or research work that might be of interest.


If this role isn’t exactly what you are looking for but feel you could add value and are interested in hearing more, please check out any other relevant roles across the company. We have several openings and would love to speak to anyone who has a background in quantitative finance and AI.

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.