Data Scientist – Commercial Analytics (355D680)

Referment; Greater London; On-site; GBP 70,000 - 110,000; Full time

Job summary

Referment is hiring its first London data scientist to turn product usage, customer and commercial data into reliable decisions across product, sales, customer success and leadership. This applied analytics role has broad ownership: replace fragmented reporting with useful models, clean data flows and clear explanations of what drives adoption, conversion, retention and revenue.

You’ll work independently through ambiguity to shape the analytics foundation for a growing B2B SaaS business.

Qualifications

• Advanced SQL skills and ability to work with complex, imperfect datasets.
• Python for data wrangling, analysis and visualization.
• Hands-on use of BI tools and product analytics platforms.
• Experience with CRM data and translating analysis into business decisions.
• Strong communication and ability to work independently through ambiguity.

Responsibilities

• Build forecasting models for usage-based revenue and cash flow.
• Analyse feature adoption, engagement and retention across customer and user segments.
• Create customer-health and churn indicators that help teams act before accounts are at risk.
• Improve CRM data quality and connect commercial records with product-usage data.
• Map the acquisition funnel, identify stalled deals and surface patterns linked to conversion.
• Automate concise reporting on revenue, usage, pipeline health and material anomalies.

Skills

Advanced SQL

Python

BI tools

CRM data

Communication

Tools

Power BI

Tableau

Job description

Referment is working with an AI software company serving investment and professional-services teams. The business is hiring its first London data scientist to turn product usage, customer and commercial data into reliable decisions across product, sales, customer success and leadership.

This is an applied analytics role with broad ownership. You’ll replace fragmented reporting with useful models, clean data flows and clear explanations of what is driving adoption, conversion, retention and revenue.

The Role

• Build forecasting models for usage-based revenue and cash flow.
• Analyse feature adoption, engagement and retention across customer and user segments.
• Create customer-health and churn indicators that help teams act before accounts are at risk.
• Improve CRM data quality and connect commercial records with product-usage data.
• Map the acquisition funnel, identify stalled deals and surface patterns linked to conversion.
• Automate concise reporting on revenue, usage, pipeline health and material anomalies.

What We're Looking For

• Advanced SQL skills and confidence working with complex, imperfect datasets.
• Python experience for data wrangling, analysis and visualisation.
• Hands-on use of BI tools and product analytics platforms.
• Experience working with CRM data and translating analysis into business decisions.
• Strong communication, intellectual curiosity and the ability to work independently through ambiguity.

B2B SaaS, fintech or enterprise-software experience would be useful where usage patterns and customer segments are complex. This could suit a commercial or product data scientist who wants ownership of the analytics foundation rather than a narrow modelling remit.