Senior Data Scientist

Senior Data Scientist

London based 3x a week

Salary up to £80,000

Looking for a Senior Data Scientist to lead the development of scalable, intelligent solutions that drive business growth across sectors like Retail, Finance, Travel, Healthcare, and Telecoms.

This company uses advanced machine learning and AI, we transform raw information into strategic insight—powering smarter decisions, improved customer outcomes, and measurable revenue growth.

With proven success supporting high-profile brands across the UK, they are entering a rapid growth phase. This is a pivotal opportunity to be part of a high-performing team as they expand their product suite and push the boundaries of applied AI.

About the Role

As a Senior Data Scientist, you'll play a hands-on, end-to-end role in the design, development, and deployment of production-ready models. You’ll bridge data science, engineering, and business strategy—building models that don’t just work in notebooks, but deliver tangible results in the real world.

This role requires more than just technical skill. You'll need to translate analytical outputs into powerful business narratives, ensuring your work is not only accurate and interpretable, but directly tied to client success.

What You’ll Be Doing

• Develop machine learning models to support use cases like:

------Forecasting (e.g. demand/revenue)

------Churn prediction, cross-sell/up-sell modelling

------Segmentation, including clustering and behavioural cohort analysis

• Build and refine datasets from both structured and semi-structured sources
• Take ownership of the full model lifecycle: data preparation, feature engineering, validation, tuning, deployment, and monitoring
• Implement and maintain ML Ops pipelines for scalable, reliable delivery
• Work closely with product managers, engineers, and clients to ensure solutions align with business priorities
• Visualise model outcomes and present insights in a clear, commercially focused way
• Stay ahead of the curve with new tools, frameworks, and modelling approaches
• Champion best practices in experimentation, version control, and reproducibility

Your experience:

• 3–5 years of experience in Data Science, Machine Learning, or Applied AI roles
• Proven ability to deploy models in live environments—not just build prototypes
• Strong Python skills and familiarity with common ML/AI libraries (e.g. scikit-learn, XGBoost, TensorFlow, PyTorch)
• Experience with cloud platforms and tools for ML Ops (e.g. AWS, GCP, MLflow, Docker)
• Commercial awareness and the ability to tie modelling work to business impact
• A passion for experimentation, storytelling with data, and continuous learning