The company and our mission:

Zartis is a global AI transformation and technology consulting partner where talented engineers and technologists work on cutting edge innovation. We partner with ambitious organizations to design, build, and scale technology solutions that deliver real impact.

Our teams bring deep expertise in AI driven platforms, secure API architectures, and cloud native engineering. You will work on meaningful projects that accelerate the adoption of advanced technologies, from strategy and discovery through to full product delivery, helping turn complex challenges into measurable outcomes.

With engineering hubs across EMEA and LATAM, and long term partnerships in financial services, healthcare and life sciences, and energy and climate, we offer opportunities to work on projects that truly matter. Here, you will not just build technology, you will drive business impact and grow your career alongside industry leaders.

The project:

Our teammates are talented people that come from a variety of backgrounds. We’re committed to building an inclusive culture based on trust and innovation.

You will be part of a small, ambitious team building an AI-native intelligence platform that combines news, social media, advanced AI and data science to help organisations identify emerging narratives, understand what is driving them and respond to reputational risk. Its intelligence layer turns millions of signals into meaningful narratives, reputation scores and actionable insights. You will work alongside the Lead Data Scientist, who provides the overall data science direction, and collaborate closely with Product and Engineering, taking ownership of specific workstreams from problem definition and experimentation through to production delivery.

What you will do:

• 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.

What you will bring:

• 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.

Nice to have:

• Experience in social media intelligence, news analytics, reputation monitoring, trust and safety or fraud detection.
• Experience with time-series modelling, anomaly detection, signal smoothing and decay functions.
• Familiarity with AWS, OpenSearch, dbt, LangChain or Langfuse.
• Experience detecting coordinated or inauthentic online behaviour.
• A track record of using AI-assisted development to materially improve personal productivity and delivery speed.

What we offer:

• 100% Remote Work
• WFH allowance: Monthly payment as financial support for remote working.
• Career Growth: We have established a career development program accessible for all employees with a 360º feedback that will help us to guide you in your career progression.
• Training: For Tech training at Zartis, you have time allocated during the week at your disposal. You can request from a variety of options, such as online courses (from Pluralsight and Educative.io, for example), English classes, books, conferences, and events.
• Mentoring Program: You can become a mentor in Zartis or you can receive mentorship, or both.
• Zartis Wellbeing Hub (Kara Connect): A platform that provides sessions with a range of specialists, including mental health professionals, nutritionists, physiotherapists, fitness coaches, and webinars with such professionals as well.
• Multicultural working environment: We organize tech events, webinars, parties, and activities to do online team-building games and contests.