Quantitative AI Scientist – Investment Strategies

Bestman Solutions
London
1 month ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Senior Data Scientist – Machine Learning -  Defence – Eligible for SC

Consultant (Data Engineer/ Scientist)

Principal Data Scientist

Lead, Data Scientist (Deep Learning), Peacock Video Streaming Service

Lead, Data Scientist (Deep Learning), Peacock Video Streaming Service

Quantitative AI Scientist – Investment Strategies | Contract | Outside IR35 | Day Rate: Flexible


We are working with a prestigious investment management firm to appoint a seasoned AI Strategist with experience applying advanced analytics and machine learning directly to investment strategies. This is a high-impact, 6-month contract role, ideal for someone from a top-tier buy-side environment who has worked alongside portfolio managers to generate alpha and optimize risk using AI and data science.


You’ll partner with the investment team, applying AI to real-world portfolio decisions and capitalizing on alternative data to drive insight.


Key Responsibilities:

  • Partner directly with investment professionals to translate strategic questions into AI-led research and actionable insights.
  • Build and deploy machine learning models and statistical techniques to identify opportunities and manage investment risk.
  • Source and analyze structured and alternative datasets (e.g., sentiment, NLP, web-scraped data).
  • Present findings clearly to stakeholders - turning complex models into practical, conviction-driven investment insights.
  • Help embed AI into investment workflows, driving innovation across strategies and teams.
  • Continuously refine and improve modeling approaches to ensure relevance and performance in dynamic markets.


Key Requirements:

  • A strong background in investment management is essential; ESG experience is a plus.
  • Experience at a top-tier investment management firm is preferred.
  • Demonstrated success in working alongside portfolio managers or investment research teams.
  • Strong programming skills in Python (preferred), R, and SQL; bonus if experienced in tools like Tableau or Power BI.
  • Expertise in machine learning, data science, and applied statistics in an investment context.
  • Advanced academic qualifications (MSc or PhD in a quantitative discipline: Stats, Maths, CS, Econ, etc.).
  • Ability to translate data into meaningful investment narratives and communicate clearly with both technical and non-technical stakeholders.


Why Join?

  • Shape cutting-edge investment strategies using AI in a highly respected buy-side firm.
  • Gain direct access to investment decision-makers and influence real-world portfolios.
  • Initial 6-month contract with a strong chance of extension based on performance and fit.

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers Education

Top 10 Best UK Universities for Data Science Degrees (2025 Guide)

Discover ten of the strongest UK universities for Data Science degrees in 2025. Compare entry requirements, course content, research strength and industry links to choose the right programme for you. Data is the currency of the modern economy, and professionals who can wrangle, model and interpret vast datasets are in demand across every sector—from biotechnology and finance to sport and public policy. UK universities have been at the forefront of statistics, artificial intelligence and large-scale computing for decades, making the country a prime destination for aspiring data scientists. Below, we profile ten institutions whose undergraduate or postgraduate pathways excel in data science. Although league tables vary each year, these universities have a proven record of excellence in teaching, research and industry collaboration.

Jobs Careers

Veterans in Data Science: A Military‑to‑Civilian Pathway into Analytical Careers

Introduction The UK Government’s National AI Strategy projects that data‑driven innovation could add £630 billion to the economy by 2035. Employers across healthcare, defence, and fintech are scrambling for professionals who can turn raw data into actionable insights. In 2024 alone, job‑tracker Adzuna recorded a 42 % year‑on‑year rise in data‑science vacancies, with average advertised salaries surpassing £65k. For veterans, that talent drought is a golden opportunity. Whether you plotted artillery trajectories, decrypted enemy comms, or managed aircraft engine logs, you have already practised the fundamentals of hypothesis‑driven analysis and statistical rigour. This guide explains how to translate your military experience into civilian data‑science language, leverage Ministry of Defence (MoD) transition programmes, and land a rewarding role building predictive models that solve real‑world problems. Quick Win: Take a peek at our live Junior Data Scientist roles to see who’s hiring this week.

Jobs

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.