Lead Data Scientist

Lead Data Scientist  The company and our mission:   Zartis is a digital solutions provider working across technology strategy, software  engineering and product development.   We partner with firms across financial services, MedTech, media, logistics  technology, renewable energy, EdTech, e-commerce, and more. Our engineering  hubs in EMEA and LATAM are full of talented professionals delivering business  success and digital improvement across application development, software  architecture, CI/CD, business intelligence, QA automation, and new technology  integrations.  We are looking for a Lead Data Scientist to work on a project in the media industry.   The project:  Our teammates are talented people from a wide range of backgrounds, and we are  committed to building an inclusive culture grounded in trust, ownership, and  innovation.  You will be part of a distributed team developing new technologies to solve real  business problems and building RiskRadar — an AI-native, decision-ready Narrative  & Reputational Risk platform. RiskRadar fuses signals from licensed content, social  media, and broadcast/video sources to produce explainable risk scores, supporting  evidence, and clear next actions.  The platform is designed for high-scrutiny brands, including financial services  organizations with strong governance, auditability, and model risk management  expectations. As a result, the work goes beyond model accuracy: it requires  interpretability, calibration, confidence, monitoring, and disciplined production  practices so customers understand when to trust the system and when to escalate  to human review.  This role sits at the intersection of data science, product, and engineering. You will  help define how risk is measured, explained, evaluated, and governed over time —  shaping scoring frameworks, entity resolution across complex data sources,  evaluation standards, and production ML/AI systems. It is a hands-on lead role,  combining technical depth with decision-making, ownership, and cross-functional  collaboration. Over time, you will also help scale the function through mentoring and  hiring.  What you will do:  ● Design and own explainable, decision-ready scoring frameworks that evolve  over time and support executive use cases.  ● Build models that clearly explain what changed, why, and with what evidence,  including confidence and uncertainty.  ● Lead entity resolution across licensed news, social, and broadcast/video data,  ensuring measurable and continuously improving quality.  ● Define evaluation standards, run disciplined experiments, and partner with  Product and Engineering to bring ML/AI features safely into production.  ● Establish and uphold production and governance standards including  monitoring, drift detection, auditability, and responsible AI practices.  ● Translate model outputs into clear verification workflows, not black-box  answers.  ● Lead cross-functional delivery and help scale the team through mentoring  and hiring, while remaining hands-on.  What you will bring:  ● 7+ years in applied Data Science / ML, with multiple production deployments  in a commercial environment (SaaS strongly preferred).  ● Proven experience leading cross-functional teams to deliver  production-ready ML/AI (even if you weren’t the people manager).  ● Strong grounding in: classification/scoring/ranking, NLP (and/or LLM  applications), statistics, evaluation, and experimentation.  ● Demonstrated ability to build explainable systems: not just performance, but  transparency, evidence, and user trust.  ● Experience designing evaluation strategies: labeled datasets, human-in-the-loop review, acceptance thresholds, monitoring and drift.  ● Comfortable operating in ambiguity with high ownership and high pace.  Nice to have:  ● Deep experience with entity resolution / record linkage at scale (probabilistic  matching, embeddings, graph-based approaches).  ● Experience building for regulated / high-governance contexts (financial  services is a plus): auditability, documentation, controls.  ● LLM evaluation and reliability methods (prompt eval, retrieval eval,  hallucination mitigation, guardrails).  ● Computer vision / multimodal experience, especially around authenticity,  manipulation detection, or media forensics.   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 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 c