- Not Specified
- Londres, Angleterre, Royaume-Uni
- CDI, Plein-temps
- Schroders Investment Management
- 23 nov. 17
Data Science Developer
Salaire : Not Specified
Lieu de travail : Londres, Angleterre, Royaume-Uni
Type de contrat : Plein-temps
The quantity of information available for investment research purposes is increasing at such a rate that traditional industry practices and skillsets are unable to absorb and process it. Global trends in digitalisation, social media, open data and technology are all creating vast streams of alternative
The quantity of information available for investment research purposes is increasing at such a rate that traditional industry practices and skillsets are unable to absorb and process it. Global trends in digitalisation, social media, open data and technology are all creating vast streams of alternative data, that have not previously been available to fund manager, and which are often highly unstructured and obscure.
The Data Insights team aims to find these new and unorthodox datasets, extract the rich, hidden information they contain and use its expertise to enhance traditional fundamental research. It is focused on applying cutting edge data science skills and technologies to enhance and complement the fundamental ‘investor’ skills of our fund managers and analysts in all parts of the asset management business including Equities, Fixed Income, Multi-Asset. The team is experiencing significant growth and now stands at 13 people since its creation in 2014. This is one of several hires new hires planned for 2017.
Background to the Data Science Developer role
In seeking to provide proprietary insights to investors across the firm, and to spread best practice in new analytical methodologies, the Data Insights Unit constantly develops new pieces of software and data processing algorithms. The Data Insights Unit is composed of people with a variety of backgrounds – computer scientists, physicists, mathematicians – that all know how to code and use code as the primary medium of communicating their ideas.
As the team grows and tackles more and more complex problems, there is a need to prototype tools quicker, increase the parallelism of existing algorithms and develop new frameworks to be used by data scientists across the organization.
Role of the Data Science Developer
To succeed in this role the Data Science Developer will need to become familiar with the existing tools and techniques used by the Data Insights Unit. They will need to show strong algorithmic thinking coupled with good grasp of mathematics and numerical computation. Proficiency with Linux and Open Source technologies is absolutely essential. It is expected that the Data Science Developer will exhibit a strong Hacker Mindset. Good organisational skills will be essential to maintain awareness of a wide variety of work-streams and datasets, although this will also be supported by existing workflow management tools within the Data Insights Unit.
• Support the Data Scientists in the Data Insights Unit by developing specialized software in Python, Bash, R and C/C++.
• Build prototypes and proof-of-concepts to expand the portfolio of algorithms.
• Optimize and/or parallelize existing code.
• Take part in the development of web-based analytical platforms and sophisticated data visualization.
• Identify and explore new technologies in the space of data science, machine learning and artificial intelligence.
• Play a key role in familiarising data scientists with software development tools and best practice.
• Work with the Data Scientists to identify processes that can be optimized or automated.
• Very good knowledge of Python.
• Proficiency in Bash scripting and a good knowledge of the Linux environment.
• Ability to work using Agile methodologies and tools (git, Continuous Integration etc.).
• Strong algorithmic thinking and problem solving.
• Finding satisfaction in solving complex technical and theoretical challenges.
• A Hacker Mindset.
• High level of organisational skills to sustain momentum in multiple work-streams
• Previous experience with data science, big data, numerical methods or scientific computing
• C/C++, R or Java experience
• Familiarity with D3 and Web Frameworks (Angular2, React, Django etc.)
• Familiarity with Big Data tools (Hive, Spark etc.)
• Experience in using Amazon Web Services or Azure