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Job Description
A Lead Data Scientist role focused on developing explainable machine learning models, entity resolution, and governance standards for a media industry project, combining technical expertise with leadership and cross-functional collaboration.
Key Responsibilities
- Design and own explainable, decision-ready scoring frameworks that support executive use cases
- Build models that explain changes, reasons, and evidence, including confidence and uncertainty
- Lead entity resolution across complex data sources to ensure quality and continuous improvement
- Define evaluation standards, conduct experiments, and collaborate with Product and Engineering to deploy ML AI features safely
- Establish and maintain production and governance standards including monitoring, drift detection, and responsible AI practices
- Translate model outputs into clear verification workflows
- Lead cross-functional delivery, mentoring, and hiring while remaining hands-on
Requirements
- 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 that ensure transparency, evidence, and user trust, not just performance
- Experience designing evaluation strategies including labeled datasets, human-in-the-loop review, acceptance thresholds, monitoring, and drift detection
- Comfortable operating in ambiguity with high ownership and high pace
- Experience leading the design and ownership of explainable, decision-ready scoring frameworks that evolve over time and support executive use cases
- Experience building models that clearly explain what changed, why, and with what evidence, including confidence and uncertainty
- Experience leading entity resolution across licensed news, social, and broadcast video data, ensuring measurable and continuously improving quality
- Experience defining evaluation standards, running disciplined experiments, and partnering with Product and Engineering to bring ML AI features safely into production
- Experience establishing and upholding production and governance standards including monitoring, drift detection, auditability, and responsible AI practices
- Experience translating model outputs into clear verification workflows, not black-box answers
- Experience scaling teams through mentoring and hiring, while remaining hands-on
Benefits & Perks
100 Remote Work
Work From Home allowance
Monthly payment as financial support for remote working
Career development program with 360º feedback
Time allocated during the week for tech training (online courses, conferences, etc.)
Mentoring program (opportunities to be a mentor or mentee)
Access to Wellbeing Hub Kara Connect with sessions with specialists (mental health, nutrition, physiotherapy, fitness coaching, webinars)
Participation in tech events, webinars, parties, and online team-building activities
Ready to Apply?
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