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Alexander Rhodes Associates Ltd logoAlexander Rhodes Associates Ltd

Data Scientist

Skills
Artificial IntelligenceBig DataData VisualizationData WranglingKnowledge Graph-Based Natural Language ProcessingKnowledge GraphsKubernetes
Role

What the job involves

The main requirements, responsibilities and hiring steps.

Requirements

  • Demonstrated 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 organizations
  • 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 ML libraries such as nltk, spacy, scikit-learn, transformers, and sentence-transformers
  • Proficient in presenting findings using visual tools
  • Ability to work with a high degree of autonomy and initiative
  • Producing maintainable, production-ready code
  • Communicative, adaptable, and resilient to change
  • Knowledge of Microservices architecture patterns
  • Knowledge of Docker and Kubernetes
  • Knowledge of Kafka as a streaming and queueing system
  • Experience with Software Engineering practices including Git version control, Test Driven Development, and Agile practices

Day to day

  • Design, develop, and deploy NLP models and algorithms to analyze large-scale text data
  • Preprocess 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 modeling, 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