Data Scientist

Churchill Frank
55000.00 GBP Annual
30 Jul 2017
27 Aug 2017
Contract Type
Full Time
A Data Scientist, you will join an established but growing team, high-visibility machine learning team that is developing and deploying solutions to some of the most challenging analytical problems. As a member of this team, the successful candidate will work to solve problems and provide solution for emerging mission-critical challenges via the utilization of emerging technologies such as:

-Data science techniques and mathematical models (machine learning, graph/link analysis, etc)
-Exposure to big data tools and technologies - Hadoop, Java


-MS or PhD degree in a quantitative discipline (e.g., statistics, operation research, computer science, mathematics, electrical engineering, industrial engineering, physics, etc.), particularly within the financial services sector
-Good relevant work experience in data science, statistical analysis and modelling, machine learning or related quantitative field
-Experience with programming software, such as Python, R, SQL, Hive, C, C++, Java, or Scala.
Solid communication skills and the ability to present deep technical findings to a business audience.

Additional Skills
-Experience with distributed computing environments, such as Hadoop, Spark or High
-Experience with probabilistic algorithms, statistical models, cluster analysis, feature selection, dimensional reduction, classification and prediction, machine learning (including supervised and unsupervised learning, deep learning, ensemble learning, and reinforcement learning), text mining or related approaches on large datasets.
-An ability to construct end-to-end data analytics and modeling workflows including data capture, cleaning, normalization, exploration, modeling design, development, and validation as well as visualization, preferably utilizing the tools previously described.
-Database management and business intelligence including SQL and NoSQL databases, such as Mongo DB or Cassandra is a plus.
-The ability to function within a multidisciplinary, global team. Be a self-starter with the ability to extract knowledge from data and to establish technical solutions based on the requirements of a non-technical audience.