Stanton House
Data Scientist
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Data Scientist
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.
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Skills needed
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- 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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