- Negotiable GBP
- London, England, United Kingdom London England GB
- Permanent, Full time
- 17 Sep 18 2018-09-17
Data Intelligence/External Data Sources
Lead Data Scientist – Data Intelligence
G-Research is a leading quantitative research and technology company. We use scientific techniques, big data and world-class technology to predict future movements in financial markets, and we develop the platform to deploy these ideas globally across multiple asset classes. We offer a dynamic, flexible and highly stimulating environment where good ideas are prized and rewarded.
We are looking for a Senior Data Scientist to join the Data Intelligence Team. You will analyse and verify the fidelity and cleanliness of diverse data sources and generate analytics to help determine the usefulness of data sets in the investment process. This is a really high profile role - you will contribute to initiatives across the Data Development Group to expand and improve the firm’s data processing pipeline and analytics suite.
You will use your strong numerate skills in Python and SQL and knowledge of statistical modelling methods to help our quant researchers evaluate a range of data sources. As there will be an opportunity to work with Big Data technologies you probably have an interest in the likes of Hadoop or Cassandra. Some knowledge of financial markets would also be beneficial.
What we’re offering is exposure to cutting-edge technologies in a high growth industry, with opportunities to learn about multi-asset class systematic investing and Big Data development in an innovative and forward-thinking firm.
This is a senior role in a growing team, so you will assume some leadership responsibilities, acting as a mentor in the technical development of other team members and help to shape the technical direction of the team
Financial and Technical Knowledge, Scientific python and pandas, advanced data analysis and statistical modelling skills developed during academic studies and career.
You'll have experience using data preparation techniques – knowledge of data cleansing, data validation, and data transformation best practices.
Ability to draw and communicate accurate and insightful conclusions from large data sets.
Strong knowledge of SQL.
An interest in Financial Markets, ideally experience working with financial data.
Proactive and resilient attitude to solving data and programming problems.
Leadership; experience managing/mentoring small teams of data analysts and evidence of strong organisational skills. Good communication and presentation skills, able to proactively build diverse internal and external relationships.