**Data Science/Consultant - £30K+ approx - London**
|Job Title:||**Data Science/Consultant - £30K+ approx - London**|
|Location:||City of London, London|
|Salary:||£30000 - £34000 per annum|
|Contact Name:||Peter Tam|
|Job Published:||over 1 year ago|
I am working with a heavyweight of the Consultancy world. Data fraud is one of the most important and interesting topics around. Data mining for missing data, linking variables together, building a story from the data..... if this sounds like your type of work - then apply to have a conversation!
I am looking for competent data professionals to aid in the development and progression of a current strong data team, to be based in London - but have potential international opportunities also.
You will expected to work with large data sets, consult with a client driven engagement team, to develop business value models and expand all fraud and credit risk activity.
You will be required to have an advanced working knowledge of SQL (essential) to analyse data and identify trends. You will need to meet demanding deadlines and have the ability to communicate between team members and client personnel.
Your role will use the most cutting edge analytical projects on the market, for effectively predicting trends for leading institutions.
This role is the perfect complement to a data science-type role.
-Ability to work both independently and as part of a team, multi-task
-Advanced technical skills in SQL, Python, R
-Msc minimum, PhD preferred (computer based discipline)
- Consultative manner
- Wanting to forge a career in advanced analytics, working with the best with a great brand behind you
I am looking for up to 10 people, so don't be shy when applying, if you showcase your ability, you will go a long way!
Key skills - SQL, Python, R, SAS, Fraud
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.
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