AI Solutions Architect

2 weeks ago

London, Greater London, United Kingdom Wealth Dynamix Full time
Wealth Dynamix: A Global Leader in End-to-End Client Lifecycle Management (CLM)

A Senior Machine Learning Scientist is required to lead our data science function, spearheading the integration of Artificial Intelligence (AI) and data-driven strategies across our CLMi and WDX1 products. With offices and clients on three continents and headquarters in London, we help relieve the burden of client management issues for wealth management and private banking firms with innovative technology.

The successful candidate will have a proven track record of leading and managing a data science or AI team, with at least 2+ years in a leadership or senior role. They will also have strong technical background in data science, including expertise in machine learning, statistical analysis, and AI technologies. Experience working with SaaS products and cloud services, particularly in deploying AI models in cloud environments like Azure, is highly desirable.

The Estimated Salary Range for this position is £80,000 - £110,000 per annum, depending on experience. Benefits include career progression opportunities, investment into the WDX Academy for new and existing employee learning and development, and exposure to multiple complex client needs.

Key Responsibilities:
  • Lead the development and deployment of AI-driven features, including predictive analytics, ML classifiers, natural language processing (NLP), and large language models (LLMs).
  • Identify and benchmark local models vs. general purpose models for individual use cases.
  • Support the development of AI-powered solutions such as Agent Frameworks to automate processes, optimize system performance, and improve operational efficiency across Wealth Dynamix products.

Required Skills and Qualifications:
  • Leadership Experience: Proven track record of leading and managing a data science or AI team.
  • Data Science Expertise: Strong technical background in data science, including expertise in machine learning, statistical analysis, and AI technologies.
  • Data Set Experience: Experience with both structured and unstructured data.
  • Machine Learning & AI Frameworks: Proficiency in Python, R, TensorFlow, PyTorch, scikit-learn, and other AI/ML tools for building and deploying models.

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