Technology Innovation Group
Data Science Engineer – Technology Innovation Group
G-Research is a leading quantitative research and technology company. By using the latest scientific techniques, we produce world-beating predictive research and build advanced technology to analyse the world’s data.
We are looking for an experienced data scientist to come and help research and test the best new data tools and technologies that money can buy.
You will be joining our Technology Innovation Group (TIG), a core part of G-Research, with a mission to continuously discover, map and test new technologies and approaches across the entire stack that might benefit the business as a whole.
TIG uses a mix of cloud-based and physical resources to explore new technologies, ranging from data science libraries and environments to cloud-native solutions and all the way to storage arrays and hardware accelerators, building proof-of-concepts and prototypes in collaboration with the rest of the business.
The responsibilities of the role include:
- Continuously scouting and evaluating new data science-related technologies and approaches
- Creating benchmarking frameworks in collaboration with the other teams to be used to quickly and effectively stress-test new technologies against the different kinds of workload we have
- Supporting technology tests and proof-of-concepts both carried out by TIG directly or in collaboration with other teams in the business
- Disseminating the results of your testing to the wider business through write-ups or blog posts aimed at raising awareness on the ever-changing tech landscape
- Attend national and international conferences to keep updated on the latest trends and services
- Use your experience – and lessons learnt while experimenting in the lab – to help defining what services, solutions or approaches TIG should test next
Who are we looking for?
We are looking for an individual with a real passion for innovation as well as a solid and proven track-record in data science engineering, ideally in a role focused on the definition of data-science pipelines and tooling.
Ideally, you will also possess:
- Strong experience in data science and machine learning frameworks
- Strong experience using programming languages such as Python, R and Spark in a data-science setting with and without interactive notebooks
- Experience with Kubernetes-based data science workflows
- Hands-on experience in processing datasets in the low-mid TBs
- Strong interest in the engineering surrounding data science and hands-on experience in building data processing pipelines
- Experience in moving data science workflows into production
- A strong background in mathematics to be able to understand the needs of quants and be able to assess new technologies and machine learning frameworks in that context
- Previous financial experience is not required, although interest in financial modelling and forecasting techniques will be beneficial when working with others who are working in this area
- A Masters or PhD degree in a highly quantitative subject (mathematics, statistics, computer science, physics or engineering) is desirable
Why should you apply?
- Highly competitive compensation plus annual discretionary bonus
- Informal dress code and excellent work/life balance
- Comprehensive healthcare and life assurance
- 25 days holiday
- 9% company pension contributions
- Cycle-to-work scheme
- Subsidised gym membership
- Monthly company events
- Central London office close to 5 stations and 6 tube lines