Senior Machine Learning Scientist – Fintech - Remote

Senior Machine Learning Scientist – Fintech - Remote Considering making an application for this job Check all the details in this job description, and then click on Apply.
Calling highly motivated, bright candidates who are looking for a career at an exciting award-winning FinTech firm!
Company: Wealth Dynamix Role: Senior Machine Learning Scientist Location: London Start Date: Nov / Dec 2025 Would you like to join one of the fastest growing FinTech firms in Europe?
We are looking for an analytical self-starter with experience in software delivery.
If you are passionate about Data Science & digital transformation and keen to learn about delivering the market-leading Client Lifecycle Management solution to the Wealth Management industry, apply now!
Who are we?
Wealth Dynamix helps to relieve the burden of client management issues for wealth management and private banking firms with innovative technology.
We provide Relationship Managers with a multi-award-winning digital Client Lifecycle Management (CLM) platform, offering 360-degree access to their client.
As a global leader in end-to-end CLM, Wealth Dynamix has offices and clients on three continents with headquarters in the UK.
What is the role?
As the Lead/Senior Data / Machine Learning Scientist at Wealth Dynamix, you will head the data science function, spearheading the integration of Artificial Intelligence (AI) and data-driven strategies across our CLM products, CLMi and WDX1.
You will lead a team of data scientists and collaborate with cross-functional teams to design, develop, and implement AI solutions that address client needs and align with the company's strategic goals.
This role requires a strong technical background in AI, machine learning, and data science, combined with leadership experience in driving data initiatives across SaaS products.
Key Responsibilities: Leadership & Strategy Team Leadership: Lead and mentor a team of data scientists, fostering a collaborative and innovative environment.
AI Strategy Development: Define and execute the AI and data science strategy for Wealth Dynamix, aligning with the overall product vision and company goals.
Stakeholder Collaboration: Partner with product managers, engineers, and client-facing teams to prioritize efforts and ensure AI solutions are integrated smoothly into the CLMi and WDX1 platforms and deliver tangible business value.
Mentorship & Development: Coach and mentor junior data scientists, providing technical guidance and support to enhance team performance and skills.
AI & Data Science Integration Product Innovation: Lead the development and deployment of AI-driven features, including predictive analytics, ML classifiers, natural language processing (NLP), and large language models (LLMs) to enhance our product offerings for clients.
Advanced Analytics: Identify and benchmark local models vs. general purpose models for individual use cases.
Oversee the creation and implementation of local domain-specific models and ML classifiers to provide insights and automation across the client lifecycle.
Automation & Efficiency: 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.
Data Collection, Analysis & Insights Data Strategy: Define the data collection, transformation, and storage strategies, ensuring the availability of high-quality data for machine learning models and analytics.
Model Development: Lead the design and implementation of machine learning models, from concept through to production deployment, ensuring they meet business and technical requirements.
Data Set Creation: Identify data set requirements for specific models and use cases, working to create appropriate datasets, including the creation of synthetic datasets.
Collaboration & Product Development Cross-Functional Collaboration: Work closely with development teams to ensure the seamless integration of AI solutions into the core products.
Feedback Loop Implementation: Create feedback loops within AI models for continuous improvement, allowing for dynamic adjustment based on new data, performance metrics, and client interactions.
Documentation & Reporting: Ensure comprehensive documentation of AI models, processes, and data pipelines, providing transparency and traceability for internal teams and external clients.
Research & Innovation Emerging Technologies: Stay current with emerging AI, machine learning, and data science technologies and frameworks, identifying opportunities to apply innovative approaches or solutions to accelerate Wealth Dynamix's proposition.
Prototyping & Experimentation: Lead the development of prototypes for new AI-driven features, iterating rapidly to test concepts and bring new ideas to market.
Best Practices Development: Establish and promote best practices for AI model development, testing, and deployment, ensuring robust and scalable implementations.
Client & Stakeholder Engagement Client Solutions: Engage with key clients to understand their AI and data-related needs, providing tailored solutions that enhance the overall client experience.
Data-Driven Consulting: Serve as a trusted advisor to clients and internal stakeholders, offering expert insights into how AI and data science can solve complex problems and create business value.
Client Reporting: Develop quantitative client-facing reports to showcase the impact of AI models and data-driven insights on their operations.
Why should you apply?
This is a fantastic opportunity to work in a growing FinTech environment with excellent career progression available.
With a global client base, the role offers an opportunity to experience a wide variety of digital transformation projects – each with their own unique requirements and opportunities.
We take career progression seriously, with investment into the WDX Academy for new and existing employee learning and development.
You will learn a lot with exposure to multiple complex client needs.
Who is best suited to this role?
Leadership Experience: Proven track record of leading and managing a data science or AI team, with at least 2+ years in a leadership or senior role.
Data Science Expertise: Strong technical background in data science, including expertise in machine learning, statistical analysis, and AI technologies (e.g., NLP, LLMs, recommendation systems).
Data Set Experience: Experience with both structured and unstructured data, and with knowledge in one or more architectural patterns such as knowledge base models and RAG.
Machine Learning & AI Frameworks: Proficiency in Python, R, TensorFlow, PyTorch, scikit-learn, and other AI/ML tools for building and deploying models.
Model & Architecture Selection: Experience in selecting and benchmarking appropriate model architectures, parameters and training strategies to optimize model performance.
Cloud & SaaS: Experience working with SaaS products and cloud services, particularly in deploying AI models in cloud environments like Azure.
Data Engineering Collaboration: Hands-on experience collaborating with data engineers to build and maintain scalable data pipelines and efficient ETL processes.
Database Proficiency: Advanced knowledge of SQL and NoSQL databases, and experience working with large datasets.
Communication & Influence: Strong interpersonal and communication skills, with the ability to influence cross-functional teams and senior leadership on AI strategy and execution.
Beneficial Skills: Financial Services/Wealth Management Experience: Previous experience in fintech, wealth management, or financial services is a plus, particularly with an understanding of client data and business needs.
CRM Data Models: Familiarity with CRM systems (e.g., Dynamics 365) and experience building models around CRM data.
Microsoft Azure Services: Experience with Azure-based services, including Azure ML, Cosmos DB, Azure Data Lake, and others.
AI Governance: Knowledge of AI governance frameworks, including model transparency, explainability, bias detection, and ethical considerations.
DevOps: Experience with CI/CD for AI and DevOps principles.
Key Performance Indicators (KPIs): Successful development and deployment of AI models that enhance product features and customer outcomes.
Effective leadership and mentorship, demonstrated by the growth and performance of the data science team.
High-quality, actionable insights that drive product innovation and business decision-making.
Continuous improvement of AI models through feedback loops, resulting in improved performance and accuracy.
Strong collaboration with product, engineering, and client-facing teams to integrate AI into Wealth Dynamix's SaaS offerings.
We believe we offer career-defining opportunities and are on a journey that will build awesome memories in a diverse and inclusive culture.
If you are looking for more than just a job, get in touch.
#J-18808-Ljbffr Remote working/work at home options are available for this role.