Applied AI ML Lead - Senior Data Scientist
Salary not listed • BOURNEMOUTH, DORSET, United Kingdom • Full-time
Posted 22d ago
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Agent Engineer
About the job
As a Vice President, Data Scientist in the Data Science team within Risk Management and Compliance, you will help shape the future of financial services by developing and implementing advanced AI solutions. You will collaborate with product, engineering, and business partners to create impactful, scalable tools that drive real business value. In this role, you will have the opportunity to experiment, learn, and innovate alongside a diverse team, leveraging your expertise in data science and finance. Together, we will deliver solutions that transform how we operate and serve our clients. Join us to make a meaningful difference and grow your career in a dynamic, inclusive environment.
Responsibilities
- Manage the end-to-end model development lifecycle, ensuring scalability and alignment with business objectives.
- Design and implement multi-agent systems, including orchestration layers, task routing, and human-in-the-loop controls.
- Implement drift monitoring and model retraining processes to maintain model performance.
- Define and implement evaluation frameworks for AI/agentic systems, covering prompt quality, agent performance, and business outcomes.
- Collaborate with senior leaders to embed AI into current workflows, driving process re-engineering and efficiency.
- Design, build, and deploy AI and data-driven applications using cloud, data mesh, and knowledge base technologies.
- Integrate advanced analytics models and applications into operational workflows for business value and adoption.
- Communicate analytical findings and recommendations to senior leadership.
Requirements
- Experience in data science, analytics, or a related field.
- Proven track record of deploying, operationalizing, and managing AI, ML, and advanced analytics models in a large-scale enterprise environment.
- Experience with AI/ML algorithms, statistical modeling, and scalable data processing pipelines.
- Experience with A/B experimentation and developing/debugging production-quality code.
- Strong written and verbal communication skills, able to convey technical concepts to both technical and business audiences.
- Scientific mindset with the ability to innovate and work independently and collaboratively.
- Ability to thrive in a matrix environment and build partnerships across various levels and locations.
- Proven experience building and deploying multi-agent systems, including use of orchestration frameworks (e.g., LangGraph, ADK), agent design patterns, and production-grade system integration.