Data Scientist

Stanton House; Greater London; On-site; GBP 90,000 - 100,000; Full time

Benefits offered by this job

Equity

On-site in London

5 days/week in office

Job summary

Stanton House in London is hiring a Data Scientist to work with the Customer Success team on product usage analytics, SQL reporting, dashboards, and data infrastructure. The role is permanent and office-based in Central London, reporting to the CTO and Head of Customer Success.

The ideal candidate will have strong SQL/Python skills, experience with BI tools, and a background in data warehousing and pipelines. This position requires 5 days in the office and offers equity and other benefits.

Qualifications

• Strong SQL and Python skills are required.
• Experience with BI or dashboarding tools (Metabase/Looker/Tableau/Retool).
• Engineering experience with data warehouse setup and data pipelines is important.
• Experience with SaaS data environments is preferred.
• Proactive, self-managing, and able to work semi-autonomously.
• Strong communication skills to explain data to non-technical stakeholders.

Responsibilities

• Generate actionable business insights from product usage, customer, and commercial data to support strategic decisions.
• Analyse product adoption and engagement trends to identify features driving retention and prioritise work.
• Develop customer health and churn prediction models using usage data.
• Improve CRM data quality and governance through audits and data integration pipelines.
• Evaluate sales funnel performance from lead to deal closure to identify bottlenecks.
• Identify patterns linking product usage to acquisition, retention, and revenue.
• Build automated reporting and dashboards for leadership on revenue, usage, and KPIs.
• Monitor business performance and surface anomalies via regular reporting.

Skills

SQL

Python

BI tools

Data warehouse

Data pipelines

SaaS data

Tools

Metabase

Looker

Tableau

Retool

Job description

Salary: £90,000 -£100,000 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

• Generate actionable business insights from product usage, customer, and commercial data to support strategic decision-making and drive company growth.
• Analyse product adoption and engagement trends to identify features that improve customer retention, highlight underutilised functionality, and provide data-driven recommendations for product prioritisation.
• Develop customer health and churn prediction models using behavioural and usage data to proactively identify at-risk accounts and support customer retention efforts.
• Improve CRM data quality and governance by auditing, cleansing, enriching, and maintaining accurate customer records through data integration and automated pipelines.
• Evaluate sales funnel performance by analysing the customer journey from lead acquisition to deal closure, identifying bottlenecks, and uncovering factors that influence conversion rates.
• Identify patterns and predictive indicators that link product usage behaviours to customer acquisition, retention, and revenue outcomes.
• Build automated reporting and dashboards to provide leadership with reliable visibility into revenue performance, product usage, pipeline health, and key business metrics.
• Monitor business performance and surface anomalies through regular reporting, enabling timely and informed decision-making.
• Partner closely with Product, Sales, Customer Success, and Leadership teams to ensure data insights inform prioritisation, customer strategy, and commercial planning.

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.