Description:
A prestigious London-based hedge fund is seeking a highly skilled Data Scientist to join its team, playing a critical role in developing sophisticated investment strategies with a focus on global macro trading and inflation dynamics. This firm collaborates exclusively with high-net-worth individuals and institutional investors, offering an opportunity to work on impactful projects in the financial markets.
In this role, you will be responsible for exploring, processing, and analysing complex time-series datasets to uncover actionable insights that directly support investment decision-making. You will design, develop, and deploy robust forecasting models leveraging advanced statistical methods, machine learning, and deep learning techniques, while ensuring compliance with industry best practices. A key part of the role will be working closely with Quantitative Researchers and Machine Learning Engineers to ensure seamless integration of models into production systems and continuous performance optimisation.
The role requires strong technical expertise and a research-oriented mindset, with a particular emphasis on building end-to-end ML pipelines and utilising cloud platforms to handle large-scale data challenges effectively.
Requirements:
MSc or PhD in Computer Science, Artificial Intelligence, Mathematics, Statistics, or related fields.
Strong programming proficiency in Python with practical experience in ML libraries and frameworks.
Proven experience in implementing and deploying end-to-end ML pipelines.
Hands-on experience with cloud computing platforms.
Ability to collaborate effectively with cross-functional teams.
Please note: Visa sponsorship is not available. Applicants must already have the right to work in the UK.
| Organization | Harnham |
| Industry | IT / Telecom / Software Jobs |
| Occupational Category | Data Scientist |
| Job Location | London,UK |
| Shift Type | Morning |
| Job Type | Full Time |
| Gender | No Preference |
| Career Level | Intermediate |
| Experience | 2 Years |
| Posted at | 2025-10-02 3:57 pm |
| Expires on | 2026-01-06 |