Abingdon_Data Scientist Internship

We are looking for the right people - people who want to innovate, achieve, grow and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their careers. Experience the challenges, rewards and opportunity of working for one of the world's largest providers of products and services to the global energy industry.,

• Entry level for professional work.
• Performs assignments designed to develop professional or technical work knowledge and abilities requiring application of standard techniques, procedures, and criteria in carrying out a sequence of related tasks.
• Limited exercise of judgment is required on details of work and in making preliminary selections and adaptations of alternatives.
• This classification is used for employees performing a designated function for an identified duration.
• Applying generative AI techniques to support data extraction, ingestion, and harmonisation from diverse geological and relational data sources.
• Exploring frontier AI technologies and contributing to prototypes using approaches such as RAG or graph-based retrieval systems.
• Develop robust Python pipelines for data manipulation using NLP and Foundation Models
• Apply geospatial libraries and techniques to subsurface geological datasets
• Implement secure coding practices and manage version control using Git
• Optimize database performance and spatial queries using PostgreSQL/PostGIS
  
  May include continuing education.
• Honors degree (2:1 or above) in data science or related field and and working towards a postgraduate degree
Role requirements
• Proficiency in Python, with a strong grasp of Python best practices
• Exposure with using Git for version control and collaboration
• Ability to use generative AI
• Ability to use of ML, NLP and Foundation Models in ETL pipelines
• Knowledge of secure coding principles
• Knowledge of PostgreSQL/PostGIS for spatial data management
• Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and data science tools (e.g., Jupyter, Pandas, NumPy)
• Ability to design, train, and evaluate supervised and unsupervised learning algorithms
• Exposure on working with large datasets, including data preprocessing
• Excellent communication skills, both written and verbal English, with the ability to communicate complex ideas clearly, strong teamwork and interpersonal skills, with a collaborative and agile mindset
• Self-motivated, detail-oriented, and capable of managing multiple tasks
Desirable Skills
• Knowledge of geological or subsurface data domains
• Abililty to develop AI models across domains such as natural language processing, computer vision, or predictive analytics
  
  Compensation is competitive and commensurate with experience.