Data Scientist - Customer Analytics

Harnham
London, UK
14 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
£65,000.0
Working hours
Regular working hours
Job source

Tech stack

Microsoft Azure Python (Programming Language) Standard Sql SQL Databases Databricks

Job description

  • Develop predictive models to solve customer and commercial challenges
  • Deliver projects across forecasting, customer segmentation, propensity modelling, and pricing analytics
  • Build solutions using Python, SQL, Azure, and Databricks
  • Present model outputs and insights to technical and non-technical stakeholders
  • Work closely with clients and internal teams throughout the project lifecycle

Requirements

Looking to broaden your data science experience across multiple industries? This is an opportunity to join a specialist analytics consultancy delivering end-to-end modelling projects for well-known organisations across sectors. You’ll combine hands-on data science with stakeholder engagement, working on projects that have real commercial impact., * Strong commercial experience in data science and model development

  • Advanced Python and SQL skills
  • Experience building predictive, forecasting, segmentation, scorecard, or pricing models
  • Experience working with stakeholders and communicating analytical findings
  • Exposure to Azure and/or Databricks
  • Consultancy experience is beneficial but not essential
  • Strong academic background in a quantitative discipline

Benefits & conditions

  • Salary up to £65,000 depending on experience
  • Hybrid working with 2 days per week in the London office
  • Broad exposure to projects across multiple industries
  • Strong technical environment focused on data science and modelling
  • Clear opportunities for professional development and progression

About the company

They are a growing data and analytics consultancy with a strong focus on predictive modelling and customer analytics. With a collaborative team of experienced data professionals, they deliver advanced solutions using modern cloud and data platforms. Their project-based environment offers excellent exposure to a wide range of business challenges and industries.

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