JOB DESCRIPTION:

Our client, a leading financial services firm, has a fantastic opportunity for an experienced Data Scientist to join the team on a permanent basis.
In this role you will be supporting the wider business in developing and deploying sophisticated models and analytical workflow, building upon the existing data engineering infrastructure to deliver reliable, high-performance analytics at scale.
With strong communication skills you will work across a number of key internal stakeholders and provide effective solutions to meet emerging business needs.

SKILLS/EXPERIENCE:

• Experienced gained within a professional or financial services firm with proven skills in data science and machine learning methodologies (e.g., regression, classification, clustering, time-series analysis).
• Strong coding skills with expertise in Python, R and strong SQL
• Experience working with Microsoft Fabric or Databricks or equivalent
• Excellent written and verbal communication skills, able to translate complex analytical findings into actionable insights for both technical and non-technical stakeholders.
• Experience working in cross-functional teams, gathering requirements from business units, and explaining technical concepts effectively.
• Demonstrates creativity in applying new techniques or technologies to improve model accuracy, scalability, and maintainability.
• Embraces feedback loops to iterate on models, incorporating new data sources or refinements to maintain relevance and performance.
• Committed to ethical data use, respecting privacy, security, and compliance regulations.
• Familiarity with governance frameworks and best practices to ensure models meet organisational and legal standards.

• Develop and deploy sophisticated models and analytical workflows within Microsoft Fabric, building upon the existing data engineering infrastructure to deliver reliable, high-performance analytics at scale.
• Provide clear, data-driven recommendations and predictive models that inform strategic decisions for end client services, external client engagement, optimisations, and operational efficiencies.
• Identify and quantify opportunities to reduce costs, streamline processes, or increase revenue, using advanced analytics to demonstrate tangible ROI and operational enhancements.
• Partner closely with product owners, data engineers, and business stakeholders to refine analytical goals, ensuring that insights are integrated into day-to-day operations and product roadmaps.
• Implement best practices for code management, versioning, and documentation, enabling continuous improvement and easier onboarding for future team members.
• Advocate for analytics and data-informed decision-making throughout the organisation, promoting the value of advanced models and ensuring that insights lead to meaningful business actions.