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Analytics Lead - Client Partner - Data

Agency - Data & Analytics
Ref: 1204 Date Posted: Monday 29 Apr 2019
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Analytics Lead - Client Partner

Analytics Consultancy

London – 55-65K

 

The Company

This Analytics Consultancy work with an impressive portfolio of clients across music, travel, energy and the eCommerce sectors.

They take pride in working in partnership with their client's and often spend 2 or 3 days a week in the client’s office, so they can provide insight face to face.

Progression and development is encouraged, and great performance is always recognised and rewarded.

They boast an extensive benefits package, plenty of perks, great working culture and social scene.

 

The Role

This Analytics Lead will partner with clients to understand their business problems with the aim of discovering solutions. Responsibilities include:

  • Delivering Analytical solutions to clients

  • Project managing and leading a team of Data Scientists, Data Engineers and Analysts to ensure the project is delivered on time and within budgets

  • Ensuring the clients are kept updated on progression of the project

  • Anticipating and dealing with challenges that emerge on the project

The amount of hands on analytics carried out by the Analytics Lead will vary depending on the project.

 

Your Profile

This Analytics Lead will have:

A proven track record with a minimum of 5 years’ experience in the field of analytics

Previous experience of working with clients and providing solutions from within a consultancy or agency.

Ability to project manage a large team.

 

How do I apply?

 

If you have experience with Digital Insight and Analytics and are excited by the opportunity of joining a cutting-edge Consultancy, then please apply for this role or get in touch with our team now to find out more.

 

Chris Devlin

Pivotal London

M: 07825 772 832

E: chris@pivotallondon.co.uk

Pivotal is an award-winning Digital Recruiter specialising in the Media, Marketing and Analytics sectors.

 

Key Skills: SQL, R, Python, Project Management, Analytics, Data Science, Data Engineering.