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Data scientist

Portalegre
Oliver Wyman
Data Scientist
Anunciada dia 11 maio
Descrição

Oliver Wyman, a Marsh (NYSE: MRSH) business, is a management consulting firm driven by deep industry insight, bold innovation, and a collaborative approach that cuts through complexity to help organizations navigate their most defining transformative moments. The Opportunity: The Data Scientist is a Data Scientist with strong data science, statistical modelling, and machine learning expertise with practical software engineering skills to build data-driven products. This role is responsible for turning complex data into actionable insights and deployable models that enable users to operationalize analytics in meaningful ways. Key Responsibilities: Partner with stakeholders to identify high-impact opportunities where data science can improve decision-making, processes, and business outcomes. Explore, clean, and transform structured and unstructured data; assess data quality, bias, and fitness-for-purpose. Develop and validate statistical and machine learning models (e.g., regression/classification, clustering, time series, etc.) and quantify uncertainty. Translate model results into clear narratives and recommendations; communicate insights to technical and non-technical audiences Create reusable data science assets (feature pipelines, model training/inference code, evaluation frameworks) with emphasis on reliability and maintainability. Experience Required: Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related quantitative field (or equivalent practical experience with demonstrable projects). 3+ years of professional experience applying data science/advanced analytics and delivering outcomes in real-world settings. Strong Python experience for data analysis and modeling Solid foundation in statistics (hypothesis testing, experimental design, regression, model evaluation, sampling/selection bias). Hands-on experience with SQL plus familiarity with No SQL databases (e.g., Mongo DB) and Databricks. Experience operationalizing analytics: reproducible pipelines, model packaging, deployment patterns, and monitoring. Comfortable with Git, CI/CD concepts, and Agile collaboration. Preferred (Good to Have) Experience with modern ML libraries and workflows (e.g., scikit-learn, XGBoost/Light GBM, Py Torch/Tensor Flow; MLflow or similar). Experience with Databricks for ML. Skills and Attributes: Excellent problem-solving and critical thinking skills required Able to frame ambiguous questions into testable hypotheses and measurable outcomes. Strong spirit of innovation, self-starter, independent, and with ability to come up with solutions to meet business problems Self-motivated with ability to work independently while also enjoying collaboration with cross-functional teams and other analysts Strong desire to learn new skills and pass knowledge acquired onto others Strong relationship building skills and ability to build alignment among customers and key stakeholders with demonstrated experience influencing without authority Ability to work effectively in a fast paced, deadline driven, highly dynamic atmosphere and react quickly to changes and shifting priorities. Effective communication skills and ability to translate numbers into a story Attention to detail and user-centric approach Please submit your CV in English. At Oliver Wyman, a Marsh (NYSE: MRSH) business, we bring deep industry insight, bold innovation, and a collaborative approach that cuts through complexity to help organizations navigate their most defining transformative moments. As a business of Marsh, we work alongside the world's leading experts across risk, reinsurance and capital, people and investments, and management consulting. Together with Marsh Risk, Guy Carpenter, and Mercer, we help organizations build resilience and competitive advantages from every angle. With annual revenue over $24 billion and more than 90,000 colleagues in 130 countries, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit, or follow us on Linked In and X .

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