About Statistical Modelling and Development

The Statistical Modelling and Development team is responsible for algorithms and model based business logic used in electronic trading in Markets. The primary purpose of this trading is to provide liquidity to clients on agency and principal basis, where either the connection to the client is electronic or provision of that liquidity requires electronic trading. The business logic includes analytics such as pre and post trade analysis and optimization.

This requires the analysis research and development of proprietary algorithms and trading business logic using data mining and statistical techniques. A significant part of the production implementation is done by the team itself.

The instruments that we currently cover include Equities, FX Spot, Government Bonds, Corporate Bonds, Rates Futures, Rates Swaps, NDFs and CDS indices.

About Data Science & Machine Learning Team

The Data Science and Machine Learning Team works on business driven projects and provides the expertise of sound and latest machine learning techniques to solve some of the most challenging data problems that they face today. This is done by following a robust data driven methodology and by working closely to the business leaders who will drive the requirements of the project. In addition to that, the group is responsible for creation of scalable modelling toolkit that can be shared amongst other data scientists. It also owns and maintains a clean core data store that gives a single point of access for any analysis or project.

Overall purpose of role:

The position will be utilized to create data science capability for AI / Machine Learning / Data Mining projects for the markets business. Successful candidate will be in charge for the creation and maintenance of a centralized modelling layer to facilitate machine learning studies. The candidate will also work closely with team of IT developers to create and maintain the underlying storage, exploration and visualization layer in the data science platform.

Key Accountabilities:

Successful candidate will be involved with creation of the following components of data science platform:

· Market Making Activity: Assist in creation of pricing and hedging algorithms as part of Barclays market making activity.

· Modelling layer: including feature engineering interface, feature engineering library, model scoring engine, model training library and the model storage layer

· Data exploration layer: build tools to allow efficient data summary statistics and graphs

· Visualization layer: build a relevant visualization layer that can allow the sharing of modelling output to other front office personnel.

Additionally, the candidate will be required to:

· Hold regular training sessions for the models created and released

· Stay in front of current technical tools available in bid data analytics

Person Specification:

· PhD, Master’s or Bachelors degree in Computer Science, software engineering, machine learning, data mining or big data analytics

· 2 to 3 years of relevant work experience in building environments for bid data analytics in real life situations

· Experience with hadoop, mapreduce, and apache spark

· Experience in working with statistical softwares such as R & MATLAB

· Experience in working with Linux, SQL, Python, Scala and JAVA

· Superior verbal and written communication skills