Research and Development Engineer in Applied Financial Mathematics

PULSALYS, innovation’s incubator and accelator of Lyon & St Etienne, builds the innovative products and services of tomorrow, transforming scientific discoveries from the laboratories of the University of Lyon into economic opportunities for companies and startups.

Created in 2018, Nyctale is a French startup that offers a SaaS platform for analysis and economic intelligence regarding cryptoassets. It develops advanced modeling tools, using machine learning and deep learning technologies applied to blockchain data graphs, to monitor the investment and usage behaviour of cryptoassets and to meet the evolving needs of the decentralized financial industry.

The Actuarial and Financial Sciences Laboratory (LSAF, University Claude Bernard Lyon 1) is a well-recognized insurance and quantitative finance laboratory. Mathematics applied to actuarial sciences is their strong point, while economic sciences broaden their vision. The SAF research lab expertise builds on an interdisciplinary expertise in applied mathematics, management science and economics to address the challenges faced by the financial and insurance sector.

As part of a partnership between the startup NYCTALE and the Actuarial and Financial Sciences research Laboratory (LSAF), PULSALYS recruits a Research and Development Engineer in Applied Financial Mathematics.

Over the past several years, many decentralized financial products and services have developed. While the media coverage and soaring prices of Bitcoin have brought decentralised currencies to the attention of the general public, their use remains mostly reserved for traditional players in the financial industry.

The development and growing use of these financial assets, which appear to circumvent some of the fiat currencies shortcomings, make the collection and analysis of economic data more difficult for market participants and financial institutions.

Having proven tools for analysing transactions and behaviours in the use of cryptoassets is crucial for investors, financial market professionals, application providers, exchange platforms and financial institutions in order to act, as appropriate, as a valuation forecasting tool, economic activity monitoring tool, market monitor, etc.

To meet the challenges of the decentralized finance market, NYCTALE is developing an economic intelligence solution, using automatic analysis and artificial intelligence algorithms applied to blockchain networks.

The LSAF and NYCTALE teams are working together to develop valuation models for different types of cryptographic assets. The aim is to obtain a better representation of their fundamental value. By taking into account the different network participant behaviours and the type of business services provided by the decentralized application that issues the cryptotoken.

The objective of the project is to apply financial mathematics models to several transactional cryptoasset databases in order to develop performance indicators for NYCTALE’s target customers.

The application of theoretical models of financial mathematics to different blockchain networks will allow NYCTALE to improve its algorithms for transactional behaviour analysis and validate, develop and refine financial indicators specifically adapted to decentralized financial products.

Integrated into the LSAF, you are the operational relay between the NYCTALE and LSAF teams.
Your missions include:
-         Produce a scientific and technical report on theoretical models of financial mathematics applied to blockchain networks;
-         Design a modelling framework suited to NYCTALE transactional databases;
-         Identify the data required for the study;
-         Develop analytic tools to study the user’s behaviour depending on the type of cryptoasset considered;
-         Build market indicators tailored to the targeted the financial products;
-         Animate regular meetings between LSAF and NYCTALE teams;
-         Actively participate in the integration and exploitation of data throughout the project.

PhD in applied mathematics, probability or statistics and data science with application to finance and economics, you have a strong appeal toward rigorous experimental approaches involving both theoretical and experimental work on real data.

You ideally have a first experience in the field of financial mathematics applied to monetary exchanges and the valuation of decentralized assets.

You are attracted through innovation and entrepreneurship and demonstrate intellectual curiosity for advanced technology areas and disruptive financial models.

You know how to conduct a research and development project with external partners; you demonstrate a real ability to adapt to a multi-stakeholder approach and know how to manage your projects independently.

You are fluent in English.