Zartis - Senior Data Scientist

• Reputation scoring: improve and validate the models powering reputation scores, building rigorous evaluation frameworks to ensure scores are accurate, stable, responsive and explainable. • Narrative intelligence: advance how related content is identified and clustered into meaningful narratives, using embeddings, graph-based clustering and human-labelled evaluations to improve accuracy and relevance. • AI-powered scoring signals: experiment with and integrate new signals, including LLM-based relevance classification and source credibility, to strengthen the quality of the intelligence. • Trust and integrity: develop approaches to identify coordinated activity, impersonation, scams and other signals that could distort the understanding of reputational risk. • Data quality and reliability: build automated validation, monitoring and safeguards to ensure the intelligence delivered is trustworthy and robust. • Own agreed deliverables end to end, design experiments, challenge assumptions, demonstrate measurable improvements and contribute production code. • 5+ years of applied data science experience, including a proven track record of developing, deploying and monitoring models or scoring systems in production. • Strong Python and SQL expertise, working with large-scale, complex datasets. • Practical experience with LLMs, including classification, prompt engineering, structured outputs and rigorous model evaluation. • Experience with clustering and graph-based techniques, embeddings, similarity measures and evaluating models where perfect ground truth doesn't exist. • Strong statistical foundations, including sampling, confidence intervals, calibration, experiment design and human-labelling methodologies. • Production engineering experience, comfortable contributing code through pull requests and working with TypeScript/Node.js and dbt alongside Python. • Hands-on experience using AI coding assistants, such as Claude Code or equivalent tools, to accelerate development, experimentation, testing and delivery while maintaining high engineering standards. • Excellent communication skills, translating complex analytical findings into clear recommendations for Product, Engineering and business stakeholders.