Senior Data Scientist
HybridPorto, Porto, Portugal
Job Summary
Partner with senior business leaders across commercial, merchandising, supply chain, and marketing to identify strategic opportunities for advanced analytics and AI. Lead the development of predictive models, machine learning solutions, and advanced analytical frameworks addressing complex retail challenges, including demand forecasting, price optimisation, customer segmentation, and assortment optimisation. Translate complex modelling outputs into clear business insights and recommendations, influencing decision-making at senior management level. Guide experimentation and test-and-learn approaches including A/B testing and causal inference to validate business hypotheses. Ensure robustness, explainability, and governance of analytical models, aligning with enterprise data and AI standards. Collaborate with data engineers and platform teams to operationalise models and integrate them into enterprise data products and digital platforms. Mentor and provide technical guidance to data scientists and analysts within the team. Contribute to the development of the organisation's advanced analytics and AI roadmap, identifying new capabilities and opportunities for innovation. Act as a trusted advisor to business stakeholders on data-driven decision making and the practical application of AI in retail. Ensure measurable business impact from deployed models, such as revenue growth, margin optimisation, cost reduction or improved customer engagement.
Required Qualifications
- Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field
- 10+ years of experience in data science, advanced analytics or applied machine learning
- Proven experience delivering end-to-end, production-grade ML solutions at scale with measurable business impact
- Background in retail, e-commerce or other consumer-facing environments
- Strong experience translating business challenges into analytical solutions, working directly with senior stakeholders
- Solid expertise in Python, statistical modelling and machine learning techniques
- Hands-on experience across the full model lifecycle, including experimentation, deployment and MLOps practices
- Experience working with cloud platforms and large-scale data environments
- Ability to communicate complex insights in a clear, business-oriented way and influence decision-making
- Strong business acumen, with a clear focus on value creation
- Experience collaborating across teams and mentoring others
- Strong problem-solving mindset and hands-on approach
- Ability to work in an international and fast-paced environment
- Fluent English (mandatory)
Desired Qualifications
- Further academic or industry certifications in AI/ML or data science
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