Data Scientist (Lisbon-Hybrid)

We're fast learners, hard workers, natural collaborators... and we Make Modern Happen!

Our ambition is to unlock the potential of our digital world so that organisations everywhere can innovate and thrive securely. We aim to achieve this goal by bringing together the world’s most talented people and the most powerful technologies, combining them to address our customers' challenges and to build something stronger together.

If you share our vision, join us!

Right now, we are looking for a Data Scientist to integrate our talent team.

Your responsibilities include:

• Collaborating with Product Owners and stakeholders to define the vision and roadmap of ML/AI-driven products with competitive advantage;
  
• Translating technical solutions into business value by defining appropriate KPIs (e.g., value/LTV, incremental margin) and corresponding operational and customer experience guardrails;
  
• Designing end-to-end decision architectures — from predictive components to optimization layers that convert predictions into actions;
  
• Designing and analysing controlled experiments (A/B tests, switchback tests) to measure causal impact with statistical confidence;
  
• Breaking down and plan solutions into epics, stories, and tasks;
  
• Building scalable cloud-based data pipelines (GCP);
  
• Developing, maintaining, and monitoring ML models in production, optimizing performance and ensuring system reliability;
  
• Measuring and maximizing the business impact of developed solutions.
  

You must have:

• Bachelor’s, Master’s, or PhD degree in a quantitative field (Engineering, Mathematics, Statistics, Computer Science, or equivalent);
  
• Relevant experience (3+ years) in developing machine learning systems or data pipelines in production environments;
  
• Strong programming and computer science knowledge, with experience in machine learning frameworks;
  
• Systems thinking: ability to decompose a business problem into a decision architecture, not just an isolated model;
  
• Experimentation and impact measurement: A/B testing / controlled experiments, sample size calculation (baseline, MDE, α/β), hypothesis testing, and strong understanding of correlation vs. causation;
  
• Technical breadth: beyond predictive modelling, comfort with optimization problems (e.g., assignment/matching, linear/integer programming) and reasoning about trade-offs;
  
• Strong communication and collaboration skills with both technical and business teams;
  
• Intellectual curiosity, critical thinking, and impact-driven mindset;
  
• Ability to adapt and manage priorities in fast-paced environments.
  

We value:

• Experience across both academia and industry;
  
• Applied causal inference;
  
• Distributed computing;
  
• Experience with combinatorial optimization / operations research in real-world contexts.
  

We offer:

• Regular professional development;
  
• Health insurance, with family package;
  
• Office facilities for meals and snacks;
  
• Regular teambuilding programs;
  
• Friendly workplace.
  

Workplace: Lisbon - Hybrid

Claranet, Make modern happen!