Senior Data Scientist: Deployable AI & Growth Analytics

VIQU Ltd; Greater London; On-site; GBP 80,000 - 120,000; Full time

Job summary

VIQU Ltd seeks a Senior Data Scientist in London to design, deploy, and explain AI/ML models that drive revenue and customer insights. You will own end-to-end pipelines, collaborate with product and engineering, and mentor junior data scientists, delivering impactful analytics across forecasting, churn, and segmentation.

You will apply Prophet for forecasting, k-means for clustering, and modern ML Ops practices to deploy scalable solutions in a cloud environment.

Qualifications

• 3-5 years of experience in Data Science, AI or ML roles.
• Hands-on delivery of end-to-end data science projects.
• Ability to translate statistical outputs into actionable business insights.
• Collaborative cross-functional work with product, engineering and clients.

Responsibilities

• Design and build ML models for forecasting, propensity, segmentation and optimization.
• Own end-to-end data workflows: feature creation, wrangling, tuning, validation and deployment.
• Operationalise models with ML Ops and integrate with cloud systems.
• Collaborate with product, engineering and client teams to align outputs with business goals.
• Interpret results visually to tell compelling stories and enable decision making.
• Experiment with new methods to improve performance and interpretability.
• Maintain code quality, reproducibility, and documentation.
• Mentor junior data scientists and lead by example.

Skills

Forecasting

Propensity modelling

Customer segmentation

MLOps

Data storytelling

Mentoring

Tools

Prophet

K-means

Cloud platforms

Job description

VIQU Ltd seeks a Senior Data Scientist in London to design, deploy, and explain AI/ML models that drive revenue and customer insights. You will own end-to-end pipelines, collaborate with product and engineering, and mentor junior data scientists, delivering impactful analytics across forecasting, churn, and segmentation.

You will apply Prophet for forecasting, k-means for clustering, and modern ML Ops practices to deploy scalable solutions in a cloud environment.