Senior Data Scientist

McLean Ross
£50000 - £70000 per annum
07 Feb 2017
07 Mar 2017
Contract Type
Full Time
The Data Scientist sifts through the data for useful nuggets of information, and then presents it to the client to allow business decisions to be made on the findings. The analysis process involves assembling and preparing the data, designing the experimental process, and executing the actual analysis.
The Data Scientist will have a strong analytic background in mathematics and the application of statistics with strong communication skills to convey complex analytical results to business sponsors of programs.

• Consult to understand customer business use cases and be able to translate them to use case specifications and vision on how to implement an analytic solution.
• Lead on analytic consulting engagements and mentor junior team members during the projects.
• Achieve defined project goals within customer deadlines; proactively communicate status and escalate issues as needed.
• Leverage knowledge in analytic and statistical algorithms to help customer explore methods to improve their business by optimizing the Analytic process and developing new capabilities.
• Perform qualification of prospects to define sales strategies based on a thorough understanding of each prospect’s analytic challenges and business needs.
• Develop demonstrations, presentations, white papers, benchmarking tools and other tools as needed to support sales and marketing.
• Advise clients and Sales on the use of Big Data solutions and Analytics on non-traditional Data Types (Clickstream, Sensor Data, Machine Data, Unstructured).


• Graduate and postgraduate research degree in a scientific discipline.
• Professional qualifications in disciplines such as Six Sigma, Business Process Modeling, DevOps and Agile considered a plus.
• 5+ years’ experience in data analysis, exploration, preparation, mining, utilizing standard tools such as R, Python, SAS, SPSS, S+, Teradata Warehouse Miner, Matlab.
• 5+ years’ experience in scripting / program languages (Perl, C, Java) for data manipulation and analysis.
• Experience with MapReduce and Spark frameworks, Hadoop and other distributed/parallel processing systems.
• Experience with Data visualization and visual story-telling.