Lead the development and governance of explainable machine learning systems for decision-making in a media industry project, mentoring teams and driving production readiness.
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
Top Skills
AI
Data Science
Machine Learning
Nlp
Python
SaaS
Statistics
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