Data Scientist

As a Data Scientist, you’ll be instrumental in shaping the future of systematic investing at the firm. This is a hybrid research-engineering position that blends rigorous quantitative research with practical implementation. You’ll work on sourcing and evaluating alternative datasets, developing bespoke machine learning models for financial markets, and building scalable, production-grade pipelines that power real-time investment signals. These signals directly inform the firm’s portfolio managers and traders, guiding investment decisions across asset classes.

We are looking for someone who is curious, technically strong, and excited by the challenge of turning complex problems into elegant, data-driven solutions. You should thrive in a collaborative, research-driven environment where innovation, experimentation, and continuous learning are at the core of everything we do.

Duties and responsibilities:

• Design and implement data science strategies that enhance the investment decision-making process.
• Identify, acquire, and evaluate alternative data sources that may provide predictive insights into financial markets.
• Develop bespoke machine learning algorithms tailored to financial use cases, such as risk forecasting, sentiment analysis, and market regime detection.
• Build, test, and deploy end-to-end data and model pipelines that operate reliably at scale.
• Collaborate closely with portfolio managers, quantitative analysts, and software engineers to ensure alignment between data science outputs and investment goals.
• Contribute to the development of internal libraries, tooling, and infrastructure to streamline data science workflows.
• Stay current with academic and industry research, applying innovative techniques where relevant.

Required experience:

• 1–3 years of experience in a data science or quantitative research role, preferably in finance or another high-impact research domain, or a recently qualified Master’s or PhD graduate.
• Track record of delivering production-ready data science solutions with real-world impact.
• Honours, Masters and/ or PhD level in a quantitative field (Computer Science, Statistics, Engineering, Applied Mathematics, Quantitative Finance or similar).
• Financial certification will be advantageous but not required.

Required Qualifications:

• Strong programming experience in Python, with proficiency in software engineering best practices (modular code, testing, version control, etc.).
• Solid understanding of machine learning, statistical modelling and time series analysis.
• Experience with cloud environments (Azure, AWS, or GCP) and distributed computing frameworks is a plus.
• Familiarity with data infrastructure (e.g., databases, ETL pipelines, containerization, orchestration tools) is highly desirable.
• Use of LLM’s and working with unstructured data is a plus.
• Experience working with unstructured or alternative data (e.g., text, news, satellite, geolocation) is a bonus.

Key competencies:

• Strong programming experience in Python, with proficiency in software engineering best practices (modular code, testing, version control, etc.).
• Solid understanding of machine learning, statistical modelling and time series analysis.
• Experience with cloud environments (Azure, AWS, or GCP) and distributed computing frameworks is a plus.
• Familiarity with data infrastructure (e.g., databases, ETL pipelines, containerization, orchestration tools) is highly desirable.
• Use of LLM’s and working with unstructured data is a plus.
• Experience working with unstructured or alternative data (e.g., text, news, satellite, geolocation) is a bonus.

Why this role:

This is a great opportunity for a Data Scientist that wants to be part of the investment management industry. The position is ideal for self-motivated individuals who thrive in dynamic environments where every day will be different and present a new exciting challenge, all while advancing their technical expertise and financial knowledge. The role offers a unique chance to contribute to the evolution of systematic investing by designing data-driven models and automating investment insights at scale. You’ll work at the intersection of quantitative research and engineering, helping to build robust, repeatable processes that enhance decision-making and reduce human bias. From alpha signal development to risk analytics and performance attribution, your work will directly support a more scalable, transparent, and efficient investment process.

 Our Culture
We pride ourselves on maintaining a fun, collaborative, and inclusive culture. Beyond the day-to-day work, we regularly host team events, social gatherings, and off-site activities that bring people together and foster a strong sense of community. We believe that great ideas come from open conversations, diverse perspectives, and a supportive environment where people enjoy working together – and having a bit of fun along the way.