Data Scientist Consultant

• Design, develop, and deploy predictive models, risk scorecards, and advanced analytical solutions.
• Build and optimise scalable data pipelines to support large and complex datasets.
• Apply statistical modelling and machine learning techniques to solve commercial risk, fraud, and business performance challenges.
• Develop innovative data products and prototype new analytical methodologies.
• Collaborate with product, engineering, and commercial teams to translate business challenges into data-driven solutions.
• Present insights and recommendations to stakeholders while maintaining high standards of data quality, governance, and regulatory compliance.

Data Scientist Consultant
Remote (UK) | £550- £625 Inside IR35 | 3 Month contract with high potentital to extend

This is a fantastic opportunity to join an innovative data and analytics organisation that is investing heavily in advanced analytics, machine learning, and cloud technologies. You will play a key role in developing next-generation predictive models, risk solutions, and data-driven products that help businesses make smarter decisions.
The Company
They are a leading data, analytics, and technology business that helps organisations unlock value from complex datasets. Through advanced analytics, machine learning, and cloud-based platforms, they deliver solutions across risk management, fraud prevention, customer insights, and business intelligence. Their teams work on innovative products that combine rich data assets with cutting-edge analytical techniques to solve commercial challenges.
The Role and Deliverables

Tech Stack: Python, SQL, Google Cloud Platform (GCP)

• Strong experience with Python and SQL for data science and advanced analytics.
• Experience developing predictive models, scorecards, and machine learning solutions.
• Strong knowledge of Google Cloud Platform (GCP) and cloud-based analytics environments.
• Experience working with commercial, financial, credit bureau, or business datasets.
• Understanding of feature engineering, model validation, auditing, and data quality frameworks.
• Knowledge of machine learning techniques including XGBoost, Random Forests, and Neural Networks.
• Familiarity with Git version control and software engineering best practices.
• Ability to communicate complex analytical findings to both technical and non-technical stakeholders.
• Experience within credit risk, commercial lending, fraud analytics, or financial services is highly desirable.
• Knowledge of regulatory frameworks relating to risk and financial services would be advantageous.

How to Apply
If you are passionate about data science, machine learning, predictive modelling, and building innovative analytics products, apply today to learn more about this opportunity.