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*Data Scientist - 45-50K - Gaming - London!*

Job Title: *Data Scientist - 45-50K - Gaming - London!*
Contract Type: Permanent
Location: City of London, London
Salary: £40000 - £50000 per annum
REF: 1954
Contact Name: Peter Tam
Contact Email:
Job Published: over 1 year ago

Job Description

*Data Scientist - 45-50K - Gaming - London!*

An established Gaming/ media company is looking to expand its data science/ BI function function by adding a Data Scientist to its ranks.

This award winning data science analytics team are looking to increasing its market stance but designing and building advanced data products, recommendation engines, personalised customer targeting and optimisation.

Reporting to the head of Data Science, this role will be to build personalised models using unstructured raw customer data, and making a story with the data for business insight.

To be part of a stronghold of data scientists and excellent PhD established professionals at the peak of their careers. You should possess a strong analytical mind with excellent data science experience, working with large customer data sets.

- MSc or PhD in a technical/ maths background
- Strong theoretical and practical knowledge of Statistics and Machine Learning techniques with the latest modern tech
- Excellent analytical, quantitative and problem-solving skills
- Strong SQL data management experinece
- Data Science experience/ Statistics (Python, SPSS, SAS, R, Scala, Spark).
- Keen interest in Data Science and the implications for business
- Data Visualisation tools: Tableau
- Excellent communication skills - good level of stakeholder management (business acumen)
- Desirable: (Map/Reduce, Hadoop, Hive, Spark)
- Competitive Salary
- Collaborative environment
- Working with data science/ analytics leaders
- Interesting and varied projects

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.