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Data Scientist

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: Stanton House
Full Time position
Listed on 2026-06-06
Job specializations:
  • IT/Tech
    Data Analyst, Data Engineer
Salary/Wage Range or Industry Benchmark: 90000 GBP Yearly GBP 90000.00 YEAR
Job Description & How to Apply Below
Location: Greater London

Salary: £90,000 base salary with equity and other benefits

On-site: 5 days working in Central London

Job Overview

Stanton House is supporting a growing Software business with their first data hire. The business is currently looking to recruit a Data Scientist to work closely with the Customer Success team by handling product usage queries, SQL-based reporting, dashboards, and data infrastructure work. The role reports hard line to the CTO and day to day to the Head of Customer Success.

The position is permanent, based in London, and expected to work in the office 5 days a week.

Responsibilities
  • Set up and maintain the data warehouse and related data infrastructure.
  • Build and maintain dashboards and data visualisations for Customer Success, leadership, and other commercial stakeholders.
  • Set up data pipelines and help establish a data warehouse, including connecting data from multiple sources that are not currently joined.
  • Own SQL across the company, including writing, maintaining, and updating queries for reporting and analysis needs.
  • Support some infrastructure and pipeline work with help from a backend engineer.
  • Work with customer success and possibly product managers to inform decisions based on usage data and the product roadmap.
  • Create analytics around feature adoption and engagement, including identifying which features drive retention and which are less used.
Skills needed
  • Strong SQL and Python skills are required, with emphasis on fundamentals.
  • Experience with BI or dashboarding tools such as Metabase, Looker, Tableau, Retool, or similar.
  • Engineering experience with data warehouse setup and data pipeline work is important.
  • Experience with SaaS, software platforms, finance, or other environments with complex usage data is preferred but not required.
  • The person should be proactive, self-managing, and able to work semi-autonomously.
  • Strong communication skills, with the ability to explain data clearly to non-technical commercial stakeholders.
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