Quantitative Researcher – AI / Machine Learning

About Our Client

Our client is a well-regarded quantitative trading company focused on developing advanced predictive models that bolster the capabilities of trading desks. The role involves leveraging sophisticated research techniques to analyze complex datasets and uncover market behaviors, translating these insights into systematic investment strategies.

They encourage applications from experienced researchers as well as recent PhD graduates from areas such as quantitative finance, technology firms, AI-focused research institutions, or academic environments. Prior experience in financial markets is advantageous but not required.

Job Responsibilities

• Create and advance machine learning models to detect predictive signals within financial and alternative data sources.
• Utilize advanced methods including deep learning, time-series analysis, natural language processing (NLP) with large language models (LLMs), and reinforcement learning in investment research contexts.
• Design and implement rigorous experiments, craft relevant features, and perform robust model assessments through backtesting and out-of-sample validation techniques.
• Examine model stability, prevent overfitting, and analyze performance variance across diverse market conditions.
• Collaborate closely with fellow quantitative researchers and engineering teams to transition research outputs into deployable, scalable solutions.
• Stay informed of novel AI advancements and assess their utility for financial market applications.

Requirements

• Possess an advanced academic qualification in relevant quantitative disciplines such as Computer Science, Machine Learning, Mathematics, Statistics, or Physics, with a preference for PhD holders.
• Recent doctoral graduates are invited to apply, as their research experience can fulfill the expertise needed for this position.
• Demonstrable strong research background in machine learning or deep learning domains, supported by doctoral studies, scholarly publications, industrial projects, or implemented models.
• In-depth knowledge in at least one specialized area like time-series modeling, sequence modeling, NLP/LLMs, or reinforcement learning.
• Proficient programming abilities in Python alongside hands-on experience with frameworks such as PyTorch, JAX, or equivalents.
• Robust foundation in mathematical and statistical principles with the aptitude to structure experiments and critically analyze outcomes.
• Experience handling extensive, potentially noisy or unstructured datasets.
• Genuine interest in financial market dynamics and the application of AI to investment challenges; prior experience in financial services is beneficial but not mandatory.

Additional Information

Applicants should send their resume quoting the role title to the representative contact at the company. Only candidates selected for further consideration will be reached.

License No: 24S2395

Registration No: R2090553