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Head of Data Science - Retail Banking - Machine Learning - R

Job Title: Head of Data Science - Retail Banking - Machine Learning - R
Contract Type: Permanent
Location: London, England
Industry:
Salary: £90000 - £130000 per annum + bonus, benefits, pension
Start Date: ASAP
REF: 3018_1496743878
Contact Name: Munveer Jabbal
Contact Email: munveer@parallelconsulting.com
Job Published: 4 months ago

Job Description

Head of Data Science - Retail Banking, Python, R, and Machine Learning

Head of Data Science - Retail Banking, Python, R, and Machine Learning

Multi-award winning, rapidly expanding business urgently requires 1 Head of Data Science to meet its ongoing growth objectives.

They operate a casual, creative and innovative working environment, with a flat management hierarchy that welcomes all ideas.

The business currently focused on huge projects and is now on the goal of continuous delivery and adopting a strong agile culture within its London office. This is the perfect time for you to join this cutting edge team to help shape the tools, technology and culture within the big data department.

As the Head of Data Science you'll be instrumental in delivering the technology that leads to wider Big Data adoption. You will have excellent Machine Learning, applied to infrastructure provisioning within Python. You will be working across many projects and leading the data science teams and be an excellent communicator who can get stuff done.

Requirements:
Retail Banking (must have)
Experience of leading teams across all levels
Machine Learning
Experience and in depth technical knowledge of Python.
Experience with delivering projects.
Stakeholder engagement
Managerial experience

As well enjoying a ground breaking working environment, you will receive an excellent basic salary, share options, health insurance, life insurance and 25 days holiday per year.






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.