Data Scientist

Location: Remote with occasional travel to head office in Wales Reports to: Chief Technology Officer The Company:

• A highly innovative AI start-up that uses advanced natural language processing and AI methodologies
• Similar to the adaptive nature of ChatGPT, their Large Language Model showcases temporal dynamics honed over five years of research & development
• Continuously learning and updating, their model provides real-time information and proactive strategy recommendations, setting a standard for accuracy and responsiveness
• The end product is a software platform that captures, refines, and delivers highly intuitive information on demand, precisely where how and when it is needed by the user

The Opportunity: The company is a start-up with a phenomenal track record of growth since launch. They have already secured relationships with many top tier brands in their field. Key to the continuing evolution of the product are challenges in document processing, data management and recall. We need a Data Scientist able to propose solutions to difficult problems in AI, Machine Learning and Natural Language Processing. This is a fantastic opportunity for a Data Scientist to apply their experience of solving abstract and theoretical AI problems to a product that will create real-world outcomes in the field of safety. The Data Scientist will be expected to work with a high degree of autonomy, using their knowledge of AI, Machine Learning and Natural Language Processing to drive product innovation. The Role:

• Design, develop, and deploy NLP models and algorithms to analyse large-scale text data
• Pre-process and clean text data to prepare it for analysis, including tokenization, stemming, lemmatization, and entity recognition
• Implement and fine-tune machine learning models for various NLP tasks such as text classification, named entity recognition, topic modelling, and language generation
• Conduct exploratory data analysis to uncover trends, patterns, and insights from text data
• Collaborate with data engineers to ensure the integration of NLP solutions into existing data pipelines and systems
• Work closely with product managers and business stakeholders to understand requirements and translate them into technical solutions
• Continuously research and stay updated with the latest advancements in NLP and machine learning to apply best practices and innovative approaches
• Communicate findings and insights through effective data storytelling, visualizations, and presentations to both technical and non-technical audiences
• Ensure the ethical and responsible use of data and NLP technologies in all projects

The Candidate:

• Demonstrable experience with Machine learning and NLP
• Experience with the application, deployment and transfer learning of open source LLMs
• Strong background in research and/or industrial roles building AI and data systems for organisations
• Development of training algorithms and management of training datasets
• Able to clearly articulate and propose ideas to non-technical stakeholders across the business
• Knowledge and experience of python with applicable matching learning libraries

1. nltk 2. spacy 3. scikit-learn 4. transformers 5. sentence-transformers

• The ability to proficiently present findings using visual tools
• The ability to work with a high degree of autonomy and initiative
• The ability to product maintainable, production ready code would be of huge benefit to anyone joining the team
• The successful candidate will be communicative, adaptable, and resilient to change
• Knowledge of Microservices architecture patterns
• Knowledge of Docker + Kubernetes
• Knowledge of Kafka as a streaming and Queueing system
• Experience with Software Engineering practices including:

1. Git version control 2. Test Driven Development 3. Agile practices The Culture: We are a remote friendly organisation open to candidates from across the UK, but at least some time each month will be required in our Wales head office to foster relationships and collaboration. We can offer flexible hours around family or healthcare commitments as we our primarily outcome based. We encourage growth and learning at every opportunity with dedicated time for training and professional development, and funding and support available for training and education. Keywords: ML machine learning AI artificial intelligence NLP natural language processing LLM large language models sentence transformers nltk spacy scikit-learn data science systems scientist python tokenization stemming lemmatization ML machine learning AI artificial intelligence NLP natural language processing LLM large language models sentence transformers nltk spacy scikit-learn data science systems scientist python tokenization stemming lemmatization ML machine learning AI artificial intelligence NLP natural language processing LLM large language models sentence transformers nltk spacy scikit-learn data science systems scientist python tokenization stemming lemmatization ML machine learning AI artificial intelligence NLP natural language processing LLM large language models sentence transformers nltk spacy scikit-learn data science systems scientist python tokenization stemming lemmatization ML machine learning AI artificial intelligence NLP natural language processing LLM large language models sentence transformers nltk spacy scikit-learn data science systems scientist python tokenization stemming lemmatization ML machine learning AI artificial intelligence NLP natural language processing LLM large language models sentence transformers nltk spacy scikit-learn data science systems scientist python tokenization stemming lemmatization ML machine learning AI artificial intelligence NLP natural language processing LLM large language models sentence transformers nltk spacy scikit-learn data science systems scientist python tokenization stemming lemmatization ML machine learning AI artificial intelligence NLP natural language processing LLM large language models sentence transformers nltk spacy scikit-learn data science systems scientist python tokenization stemming lemmatization