Data Scientist - Customer Analytics

DATA SCIENTIST - CUSTOMER ANALYTICS London (Hybrid, 2 days per week) | Up to £65,000 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.

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.

The Role 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 Your Skills & Experience 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 What They Offer 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

How to Apply

Apply today to learn more about this Data Scientist opportunity.