Principal Data Scientist

• Serve as Vortexa’s subject-matter authority for data science
• Design, implement and deploy advanced AI/ML methodologies and production-grade systems
• Define success for frontier problems without obvious baselines or established benchmarks
• Improve live predictions in collaboration with production-owning pods
• Own substantial projects end-to-end, from initial exploration through long-term maintenance
• Identify emerging approaches, formulate hypotheses, design rigorous experiments and evaluate new techniques
• Translate research into practical real-world solutions
• Build Data Science capability through technical review, pairing, mentoring and setting working standards
• Lead the Data Science Guild by setting its technical agenda and facilitating cross-practice discussions

Requirements

• Experienced enough to lead complex projects across Data Science, Machine Learning and AI while remaining hands-on and capable of building and deploying production-grade models
• Strong theoretical and mathematical foundations in ML/AI, with the ability to engage critically with current research and emerging methodologies
• Comfortable owning code to production standard across the full ML lifecycle: experiment design, model development, validation, deployment, monitoring and long-term maintenance
• Deeply trained in a quantitative discipline; ideally educated to PhD level in Computer Science, Statistics, Applied Mathematics, Physics or a related field
• Equivalent depth developed through industry experience is equally valued; expertise matters more than the credential
• Fluent in Python
• Strong experience with regression and classification, clustering, time-series analysis, anomaly detection, sequence-to-sequence architectures and stochastic optimisation
• Able to solve ambiguous problems independently and determine next steps without waiting to be directed
• Able to develop team capability through technical review, pairing, mentoring and high standards
• Able to explain modelling trade-offs clearly to non-technical stakeholders, set expectations, negotiate scope and maintain a technical position under pressure
• Curious about energy markets and comfortable challenging and being challenged by analysts and technologists
• Experience in energy, quantitative trading, frontier AI techniques, transformer architectures, generative models or agentic AI is an advantage

Core Competencies

Demonstrates expertise in Data Science and Machine Learning, with a strong foundation in theoretical and mathematical principles. Capable of leading complex projects, developing production-grade models, and translating research into practical solutions while mentoring and building team capabilities.

Highest-signal resume keywords

• Machine Learning
• Artificial Intelligence
• Python Programming
• Model Development
• Data Science Leadership

ATS Optimization Keywords

Hard Skills

• Regression Analysis
• Classification
• Clustering
• Time-Series Analysis
• Anomaly Detection
• Stochastic Optimisation
• Experiment Design
• Model Validation
• Model Deployment
• Monitoring

Soft Skills

• Problem Solving
• Mentoring
• Communication
• Collaboration
• Curiosity

Industry Keywords

• Energy Markets
• Quantitative Trading
• Frontier AI Techniques
• Transformer Architectures
• Generative Models
• Agentic AI