Python Data Scientist (Quantitative Finance)

OTS Research
Greater London
1 year ago
Applications closed

Related Jobs

View all jobs

Applied AIML Lead- Python & Data Science Engineering

Data Scientist

Senior Data Scientist - AI Practice Team

Senior Data Scientist (Clinical Data Analytics)

Senior Data Scientist - AI Practice Team

Data Scientist

Python Data Scientist (Quantitative Finance)


We are seeking a highly skilled and motivated Python Data Scientist to join our dynamic team with a minimum of 4 years of work experience. The ideal candidate will have extensive knowledge in quantitative finance, with a focus on FX or cryptocurrency trading. This position requires a strong foundation in Python programming and linear models, as well as proven experience in data mining.


*Key Responsibilities:*

- Collaborate with quantitative researchers to develop, tune, and refine trading models, ensuring optimal performance and accuracy.

- Apply expertise in quantitative finance to analyse complex data sets and extract meaningful insights that can directly impact trading strategies.

- Utilise Python to implement and maintain robust data analysis tools and algorithms.

- Conduct extensive data mining to identify new trading opportunities and trends in the FX and cryptocurrency markets.

- Develop and test linear and non-linear modelling techniques to improve predictive accuracy and model performance.

- Prepare detailed analytics reports and communicate findings to stakeholders and team members to support data-driven decision-making.


*Requirements:*

- Proven experience as a Data Scientist with a strong background in Python programming.

- Advanced knowledge in quantitative finance, particularly in FX or crypto trading.

- Proficiency in linear models and their application in financial modelling.

- Demonstrated experience in data mining and handling large, complex datasets.

- Ability to work closely and effectively with quantitative researchers and other team members.

- Strong analytical skills with a keen attention to detail.

- Excellent communication and presentation skills.

- This will be a remote position initially and then the candidate will be relocated to Dubai, UAE. Must be willing to relocate.


*Preferred Qualifications:*

- Advanced degree in Mathematics, Statistics, Computer Science, or a related field.

- Experience with additional programming languages or analytical tools is a plus.

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.