Top Data Science Jobs in Lisbon

IT internship program offering classroom, on-the-job, and professional training across software development, DevOps, system administration, business intelligence, analytics, cybersecurity, databases, data engineering, and data science. Interns will gain practical experience within Natixis teams in an international banking environment. The program requires full-time availability in Porto and includes hybrid office attendance.

Leads a globally distributed data science team while developing advanced analytics and machine learning solutions for marketing campaign targeting, execution, and measurement. Responsibilities include researching AI technologies, building and monitoring predictive models, designing large-scale data pipelines, applying machine learning and deep learning methods, establishing responsible AI practices, mentoring data scientists, and communicating insights and roadmaps to business and product stakeholders.

Drive application security and regulatory compliance through vulnerability management, CI/CD and Azure-based practices, security scanning, compliance testing (DR, pen tests), and developer best-practice governance. Report on product compliance, lead technical change (GenAI, FinOps), and support remediation and patching efforts.

Lead independent product analytics investigations across acquisition, activation, usage, customer experience, and the broader customer journey. Apply statistical analysis, causal inference, experimentation, and data science modeling to uncover product issues, opportunities, churn drivers, and growth insights. Analyze structured, unstructured, and AI-specific data; size opportunities; measure engineering productivity; and translate findings into actionable recommendations for Product, Engineering, Growth, commercial teams, and executives.

Implement and support Microsoft Customer Insights projects: integrate data sources, configure unified profiles, build customer segmentation and behavioural analyses, develop and execute test strategies, connect Customer Insights with Dynamics and other Microsoft platforms, support Sales alongside Corporate IT/T2D, and create dashboards using Power BI.

Leads data science and AI initiatives that solve complex business problems across Novartis. Responsibilities include data management, statistical analysis, machine learning, visualization, stakeholder storytelling, technology evaluation, exploratory analysis, project coordination, resource planning, governance, and potentially team leadership. The role also contributes to scientific publications, conferences, and advanced analytics strategy while ensuring quality, ethical, safety, and regulatory standards.

Develop GreyNoise’s cybersecurity channel business across Europe by recruiting and activating partners, building joint business plans, enabling partner teams, generating qualified pipeline, and co-selling enterprise and government opportunities. The role manages partner relationships, channel strategy, revenue targets, forecasting, commercial negotiations, partner reviews, technical enablement, demand generation, and cybersecurity event representation.

Own the Mapping & Content product domain end to end, including strategy, prioritization, economics, and outcomes. Lead efforts to match hotel rooms and content across suppliers, languages, and formats with high accuracy and coverage. Partner closely with engineering and data science teams on entity resolution, search, matching, catalog, identity, recommendation, and content-quality problems. Identify high-value failures, make trade-offs between precision and coverage, and help build Nuitee’s product organization in a fast-moving environment.

Analyze complex healthcare datasets using statistical, machine learning, clustering, segmentation, and time-series techniques. Translate findings into actionable business insights, contribute to custom research studies, and support research reports and presentations. Collaborate with researchers, consultants, and technical experts to deliver analytics solutions for healthcare and life sciences stakeholders.

Analyze complex healthcare datasets using statistical, quantitative, and machine learning techniques. Identify drivers, assess changing conditions, forecast trends, conduct custom research studies, and translate findings into actionable business insights. Collaborate with researchers, consultants, and technical experts while contributing to research publications, reports, and presentations.

Manage the Data Science team’s delivery, people development, project planning, and technical standards. Lead model validation, reproducible software practices, Agile delivery, and transition of prototypes into deployable products. Coordinate with scientific, engineering, biology, photonics, and clinical teams. Develop training programs, support hiring, report progress to leadership, and define the company’s strategy for adopting AI coding assistants, LLM agents, AutoML, and experiment tooling safely and effectively.

Manages and mentors Data Scientists while overseeing the full lifecycle of machine learning models powering real-time payment decisions. Defines the Payment Intelligence roadmap, translates complex data challenges into business goals, and partners with engineering, product, and design teams to deliver production solutions. Communicates ML strategy and technical trade-offs to senior leadership. The role requires hands-on expertise in Python, SQL, cloud-based ML, and complex model architectures, with payments or fraud prevention experience preferred.

Build Paddle’s data science function and production decisioning systems from the ground up. Prioritize high-value use cases, personally deliver the first ML or agentic system, and own deployment, monitoring, experimentation, reliability, governance, and financial impact. The role will establish the production ML stack, collaborate across Product, Engineering, Risk, Finance, and Compliance, then hire and lead data scientists and ML engineers. Experience with regulated transactional domains, production ML operations, experimentation, and executive stakeholder management is required.

As an AI Product Manager, you will lead the development of AI-powered features, collaborating with cross-functional teams to align products with user needs and business goals, while overseeing the product lifecycle.

Lead GTM strategy and product positioning for key products, create messaging and content, run campaigns and launches, analyze market and competitive trends, and collaborate cross-functionally to drive adoption, pipeline growth, and customer engagement.

The Lead Golang Software Engineer develops server solutions, leads technical designs and code reviews, mentors colleagues, and ensures the quality of engineering practices in the Commercial Systems unit.

Lead strategic product roadmaps, conduct market intelligence, manage pricing strategy, apply data analysis, and mentor teams while collaborating with cross-functional partners.

Manage curriculum development for data science and engineering, collaborate with instructors, create content, and drive improvements based on learner feedback.

As a Curriculum Manager, you will manage content development for the data science and engineering curriculum, collaborating with instructors and teams to enhance learning experiences.

Data Scientists at QuantCo will analyze data, build machine learning models, and communicate results to stakeholders, aiming for impactful solutions.

As a Data Science Intern, you'll identify frameworks for data-driven business challenges, transform datasets, run analyses, build machine learning models, and communicate results.

As a Curriculum Manager, you will manage the content development lifecycle, collaborate with instructors, and improve data science curriculum, ensuring technical accuracy and pedagogical effectiveness.

The Curriculum Manager will oversee the content development lifecycle, recruit instructors, design curriculum, assess course performance, and improve data science and engineering content.