Hybrid Data Scientist - High-Impact ML & Growth

Harnham - Data and Analytics Recruitment; Liverpool; Hybrid; GBP 50,000 - 61,000; Full time

Benefits offered by this job

Hybrid work (3 days onsite)

Benefits

Job summary

Harnham - Data and Analytics Recruitment in Liverpool is seeking a Data Scientist to join a growing data science team within a large UK organisation investing in Data & AI. You will work on customer-focused ML projects, scale capabilities, and deliver models with real commercial impact.

The role spans the full lifecycle from problem definition to deployment, collaborating with analysts, engineers and business stakeholders.

Qualifications

• Strong commercial Data Science experience.
• Excellent Python and SQL skills.
• Experience with machine learning and statistical modelling.
• Proven experience deploying models into production.
• Strong stakeholder management and communication skills.
• Exposure to Azure or GCP is advantageous.
• Experience with customer analytics or forecasting is beneficial.

Responsibilities

• Build and deploy predictive and statistical models
• Develop customer segmentation, customer lifetime value, and churn models
• Deliver forecasting and customer analytics solutions
• Work across the full Data Science lifecycle from problem definition to deployment
• Partner with analysts, engineers, and business stakeholders
• Present insights and recommendations to non-technical audiences
• Support the development of Data Science best practices and capabilities

Skills

Python

SQL

Machine learning

Statistical modelling

Production deployment

Stakeholder management

Communication

Azure

GCP

Customer analytics

Tools

Azure

GCP

Job description

Harnham - Data and Analytics Recruitment in Liverpool is seeking a Data Scientist to join a growing data science team within a large UK organisation investing in Data & AI. You will work on customer-focused ML projects, scale capabilities, and deliver models with real commercial impact.

The role spans the full lifecycle from problem definition to deployment, collaborating with analysts, engineers and business stakeholders.