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data science

Make smarter decisions, improve risk assessment, and elevate your operations.

Customise to suit your needs

Achieve more, with less code

Quantifi’s data science-enabled platform enables you to automate and ‘outsource’ the task of manually collecting and processing data. Users can focus on implementing the required custom business logic, complimentary to the functionality of the platform and significantly reduce delivery times. This means you can do complex data analysis and flexible reporting using Python, Jupyter Notebooks and other popular data science tools. Integrated with our advanced model library, you will benefit from complex data-driven analysis, strategy back-testing, ad hoc portfolio what-if scenarios – all using mixed data sets from diverse sources.

Demonstrate alpha and support tailored investment solutions.

Improve investment decisions with machine learning and AI.

Lower operational costs with an integrated self-service architecture.


Improve investment decisions


Cloud-Native Technology

Cloud-Native Technology

Provides clients with an environment that optimises operations for greater flexibility, scalability and agility.
Mix Diverse Data Sources

Mix Diverse Data Sources

Easily mix diverse data sources for complex reporting, including structured & unstructured data.

Flexible Self-Serve Reporting

Flexible Self-Serve Reporting

BI and visualisation which includes use of third-party tools such as Power BI and Tableau.

Scalable Performance

Scalable Performance

Processing capabilities can easily scale up or down to accommodate a client’s demands & business needs.

Complete Ad-hoc Analysis

Complex Ad-hoc Analysis

Perform complex ad-hoc portfolio level analysis and what-if analysis in a sandboxed environment.
Modern Python API

Modern Python API

Combine Quantifi risk results, data and models with other data science & machine learning tools.

Open APIs

Extend and customise

Foster innovation with a powerful, low-code development environment that empowers traders, risk managers, and quants to run complex analysis and extend the functionality of the solution.

One of the key benefits is the ability to call Quantifi from Python. This makes it easy for us to extend the high-level functionality of the model library, which gives us an array of manipulation capabilities to perform advanced analysis.

Jeysson Abergel, Head of Trading and Macro Strategy at Arini

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Make better investment decisions

Providing clients with the ability to do complex data analysis and flexible reporting using popular data science tools. Integrated with Quantifi’s proven portfolio management solution, users benefit from complex client-driven analysis, strategy back-testing, ad hoc portfolio what-if analysis – all using mixed data sets from diverse sources.


Innovative thinking


Leveraging data science for next generation risk & PnL

Over the last few years, there has been a step change in the role of data and technology in trading, risk management and investment decision-making. Firms are deploying data science tools to improve risk assessment and business response strategies, and bring more rigour to their operations.


Front-office reboot: how new technology, machine learning and data science are reshaping trading

Learn how traders are structuring trades using new technology, how cloud is impacting trading and how machine learning is driving market making and decisioning.


How Data Science is Transforming Finance

The past decade has seen the rise of emerging technologies across the financial industry and beyond. There are now synergistic groups of technologies that are operating at scale and will further accelerate digitisation, boost resilience and drive operational efficiencies.

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Technology tailored to you

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