Junior Machine Learning Scientist - Fintech – Remote

Junior Machine Learning Scientist NLP-LLM - Fintech – Remote Junior Machine Learning Scientist wanted as our team is growing fast! Calling highly motivated, bright candidates who are looking for a career at an exciting award winning FinTech firm! Company: Wealth Dynamix Role: Junior Machine Learning Scientist Location: London Start Date: June / July 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 as a Junior Machine Learning Scientist. If you are passionate about digital transformation and keen to learn about delivering the market leading Client Lifecycle Managing 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. We are a global leader in end-to-end CLM, Wealth Dynamix has offices and clients in three continents with headquarters in the UK. What is the role? This job description outlines the scope of the role for a Junior ML Scientist – NLP at Wealth Dynamix. While responsibilities may evolve, the core of the role is to support the development and deployment of AI-powered features, with a focus on natural language processing (NLP) and large language models (LLMs) that enhance our CLMi platform. This role provides a strong foundation for candidates who want to grow in applied data science, especially in real-world, production-driven AI systems — with mentorship from a senior team and opportunities to engage with innovative tooling. Main Purpose of Role As a Junior Data Scientist, you will assist in designing, building, and evaluating ML models that power key components of our product, such as intelligent assistants, document analysis, and insight extraction. You’ll contribute to experimentation, data preparation, and evaluation tasks, and gain exposure to MLOps/LLMOps processes in a on premise & SaaS deployment environment. Core Responsibilities Model Development & Experimentation Contribute to building NLP models for tasks such as sentiment analysis, entity recognition, classification, summarisation, and retrieval-augmented generation. Assist in model evaluation using relevant accuracy, precision, recall, and ranking metrics — including for LLM-based systems. Data Science Support Prepare datasets, engineer features, and conduct exploratory data analysis (EDA). Use statistical techniques to uncover insights and inform model development. Uphold security best practices to protect systems, data, and people. Research & Prototyping Support rapid prototyping and iteration using libraries like Hugging Face Transformers, spaCy, and scikit-learn. Contribute to documentation and presentation of findings to internal stakeholders. Model Integration & Learning Learn from and assist with the deployment and testing of ML models in cloud and on-premise environments. Gain familiarity with the MLOps/LLMOps lifecycle, including pipelines, reproducibility tools, and evaluation challenges. 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 have the flexibility to work from home, in the office or remotely. Who is best suited to this role? Strong foundation in statistics, machine learning, and NLP techniques. Proficiency in Python, including tools like pandas, NumPy, matplotlib. Familiarity with ML/NLP libraries such as PyTorch, TensorFlow, spaCy, Hugging Face Transformers. Basic understanding of LLM architectures, prompt engineering concepts, and evaluation challenges. Clear and effective communication and presentation skills. Strong problem-solving ability, attention to detail, and willingness to take initiative. Proven ability to work collaboratively in cross-functional teams. Preferred Strengths Hands-on experience building or evaluating NLP models, e.g. sentiment analysis, classification, or summarisation. Familiarity with evaluating ML models in production or pre-production settings. Exposure to deployment processes, including working with cloud platforms (Azure preferred) or containerised services. Enthusiasm for working in a fast-paced or agile product environment where experimentation is encouraged. What you will gain? Mentorship and hands-on experience with applied NLP and LLM projects in a real-world product. Exposure to ML engineering and deployment workflows, including MLOps tools and practices. The chance to contribute to meaningful features used by wealth management professionals across the globe. A supportive, collaborative environment where you can develop deep technical skills and industry understanding. 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.