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Data Scientist

Job Title: Data Scientist
Contract Type: Permanent
Location: City of London, London
Salary: £70000 - £80000 per annum
Start Date: ASAP
REF: 09/12
Contact Name: Zoe Hallam
Contact Email:
Job Published: over 1 year ago

Job Description

A fantastic opportunity has arisen to join an exciting new VC backed start-up that will analyse customer data to provide valuable insight and market intelligence to major sports clubs all over the world.

Our client is looking to recruit a Data Scientist who will work with the Development & Architect team to use cutting edge technology to derive key observations and provide actionable insights to client data. As the core of the team, the company will be based around your decisions and will ultimately pave the way to revolutionising the sport and technology industry.

- Work alongside the Chief Architect to translate the business goals onto the
desired technology stack
- Understand the clients analytical requirements and translate them into
statistical models
- Understanding the clients data to gain statistical observations with a view to
provide actionable insights
- To stay up to data on the latest analytical techniques and platform technologies, understand business objectives and provide relevant solutions

Essential Skills Required:
- A sound understanding of exploration tools such as Python and R
- Experienced in unstructured data analysis
- Knowledge of various statistical techniques such as segmentation, regression, predictive
analytics and Machine Learning
- Experience in data mining and scripting, and tools such as Hive or Pig
- Proficient in working with Spark and/or knowledge of Scala code

This is a great opportunity to join a fast growing and innovative new start up. If you have a passion for sports, technology and great career progression, then apply now!

Parallel Consulting is a multi-awarding winning, global leader in Analytics & Data Science recruitment.
With over 12 years expertise, we assist our clients within Analytics, Customer & Marketing Insight, Web Analytics, Big Data, Data Science, Credit Risk and BI.