Data Scientist

• Collaborate with cross-functional teams to understand business requirements and translate them into AI/ML solutions
• Design, develop, and deploy AI models and algorithms for classification, regression, clustering, and recommendation
• Preprocess and analyze large datasets to extract meaningful features and insights for model training
• Experiment with machine learning techniques and algorithms to improve model performance and accuracy
• Implement and optimize AI/ML models for scalability, efficiency, and real-time inference
• Conduct rigorous testing and validation of AI models for robustness, reliability, and generalization
• Stay updated on AI/ML research, frameworks, and tools and evaluate their applicability
• Collaborate with data engineers, product owners, business stakeholders, and external partners
• Ensure models are explainable, auditable, and aligned with data privacy and regulatory requirements
• Mentor and support junior team members

AI/ML Data Scientist

• Collect, validate, and maintain data from internal and external sources
• Analyze clinical trial, site, investigator, and operational data to identify trends, patterns, and improvement opportunities
• Develop and maintain standard reports, dashboards, and data visualizations
• Support feasibility assessments with data summaries, analyses, and insights on study requirements, site performance, recruitment trends, and therapeutic areas
• Collaborate with Operational Strategy, Clinical Operations, Business Development, and other stakeholders to deliver timely analyses
• Perform data quality reviews and resolve inconsistencies and gaps
• Improve data collection, reporting, and analytical processes
• Support evaluation and integration of new data sources, tools, and technologies
• Maintain documentation for data sources, methodologies, reporting processes, and best practices
• Develop and update reporting templates and analytical tools
• Provide ad hoc analyses and reports
• Monitor operational and feasibility metrics and communicate findings
• Support process improvement initiatives using data
• Perform other duties and special projects as assigned

Manager, Data Intelligence

• Collect, process, and analyse structured and unstructured datasets using Python, SQL, and modern data science techniques
• Develop, validate, and deploy machine learning and statistical models for forecasting, customer analytics, and predictive business use cases
• Perform feature engineering, data preparation, and model optimisation
• Design and maintain analytical workflows and data pipelines, collaborating with Data Engineering teams when required
• Identify trends, patterns, risks, and opportunities in complex datasets
• Translate analytical findings into actionable recommendations and present results to technical and non-technical stakeholders
• Collaborate with clients, business stakeholders, and cross-functional teams to deliver data-driven solutions
• Support data science best practices, modelling methodologies, and reusable analytical frameworks
• Apply predictive analytics, customer analytics, and advanced statistical techniques to business challenges
• Contribute to client-facing analytics projects from discovery through implementation

• Partner with senior stakeholders across Marketing, Revenue Operations, Finance, and Product to define and solve ambiguous, high-impact problems using advanced data science methodologies
• Apply predictive modeling, causal inference, marketing attribution models, value-based models, and customer segmentation
• Establish technical and analytical standards through reviews, documentation, enablement, and tooling
• Lead multi-team initiatives by defining strategy, architecture or approach, and success metrics
• Mentor and coach analysts and build analytical capability
• Own mission-critical workstreams end-to-end, from framing business questions to shipping models, forecasts, and recommendations
• Deliver measurable improvements to company-level KPIs such as CAC, LTV, churn, pipeline conversion, and revenue forecast accuracy
• Anticipate risks and unblock teams to ensure analytics projects ship reliably and on time
• Advise senior leaders by translating complex analyses into clear, actionable recommendations that shape strategy

Senior Data Scientist

• Lead machine learning projects from hypothesis formulation and task setting through measurable business impact
• Own the end-to-end ML cycle, ensuring fast time-to-market and maintaining model quality in production
• Collaborate with Data Engineers on production data pipelines
• Collaborate with Data Analysts to understand business context, define metrics, and design and evaluate A/B tests
• Translate complex travel and B2B business problems into mathematical and machine learning modeling tasks
• Design and deploy scoring models predicting the probability of search queries converting into bookings
• Model how conversion likelihood changes dynamically with price and availability
• Optimize the search-to-book funnel
• Optimize margin/profitability and minimize operational incidents while factoring in B2B client preferences
• Predict the likelihood of rates/offers becoming stale before booking to balance data accuracy, speed, and system load
• Develop, train, and validate machine learning models to test product hypotheses and improve the B2B user experience

Data Scientist jobs in Portugal

AI/ML Data Scientist

Manager, Data Intelligence

Data Scientist

Senior Data Scientist

Senior Data Scientist – Look-2-Book