Data Scientist

Description

Job Summary: As a Data Scientist, you will develop analyses, statistical models, and machine learning solutions to support decision-making, value generation, and the evolution of the Auren Data & AI Platform. Key Highlights: 1. Practical application across the entire solution lifecycle, from definition to industrialization. 2. Work within a living ecosystem where the future of business is created. 3. Transform business problems into actionable recommendations. #### **About the Data Scientist Role** **Join a dynamic ecosystem where the future of business is created and experienced every day. Be part of this transformation!** At LUZA Group, passion, perseverance, and the drive to surpass limits define our path to success. Founded in 2006, we are a Portuguese multinational with over 1,200 talented professionals and a significant business volume. With presence in strategic markets including Portugal, Spain, Morocco, Brazil, Mexico, the United States, and China, we deliver innovative solutions in engineering, IT, design, consulting, Industry 4.0, training, and recruitment. Everything we do is powered by the talent of our people. **This is a moment of growth and opportunity. The future belongs to visionary minds. Join us!** **Data Scientist** **Position Objective** The Data Scientist will develop analyses, statistical models, and machine learning solutions to support decision-making, business value generation, and the evolution of the Auren Data & AI Platform. This role requires the ability to translate business problems into analytical hypotheses, experiments, models, and actionable recommendations, working collaboratively with data, technology, business, and governance teams. Practical involvement across the full solution lifecycle is expected—from problem definition through validation, documentation, and eventual industrialization in production environments.  **Responsibilities** Translate business needs into analytical problems and testable hypotheses. Conduct exploratory, statistical, and predictive analyses to identify patterns, opportunities, risks, and value levers. Develop machine learning models—including classification, regression, clustering, time series, forecasting, and anomaly detection—where applicable. Perform data preparation, cleaning, transformation, and enrichment for analysis and modeling. Select, test, and compare analytical approaches considering accuracy, interpretability, cost, scalability, and applicability to the business context. Evaluate model and experiment results, proposing improvements and adjustments based on technical and business metrics. Support the definition of reliable variables, features, and datasets for analytical and AI use cases. Collaborate with data architects, data engineers, AI engineers, and end-user areas to enable end-to-end solutions. Document hypotheses, assumptions, methodologies, results, and limitations of developed analyses and models. Support the transition of prototypes into scalable and sustainable solutions within the corporate environment. Use generative AI and automation tools, where appropriate, to accelerate exploration, prototyping, code generation, and documentation—always with technical validation.  **Technical Requirements** Experience using Python for data analysis and model development. Strong knowledge of SQL and data manipulation in structured databases. Hands-on experience with libraries and frameworks such as pandas, numpy, scikit-learn, matplotlib, seaborn, or equivalents. Knowledge of applied statistics, probability, statistical inference, and experimental design. Experience with supervised and unsupervised machine learning techniques. Ability to interpret model performance metrics and translate technical results into business language. Familiarity with best practices for code organization, version control, and documentation. Familiarity with enterprise data environments and analytical platforms. Ability to work with data from multiple sources, with attention to quality, consistency, and traceability.  **Preferred Qualifications** Experience with time series, demand forecasting, optimization, anomaly detection, or predictive maintenance problems. Experience with projects in regulated, industrial, or critical infrastructure sectors. Knowledge of cloud tools and modern data platforms. Experience with MLOps, model versioning, and production deployment. Hands-on experience with generative AI, embeddings, LLMs, or copilot tools to accelerate analytical work. Experience with data visualization and BI tools such as Power BI or similar. Knowledge of explainability, interpretability, and responsible AI techniques.  **Expected Profile** We seek a professional with strong analytical reasoning, intellectual curiosity, and methodological discipline. The candidate must be autonomous in investigating problems, structuring analyses, and supporting conclusions with evidence. Collaboration skills with both technical and business stakeholders, strong communication, organizational ability, and a results-oriented mindset are expected. It is also important to demonstrate maturity in handling ambiguity, prioritizing value-generating activities, and evolving solutions incrementally—without compromising technical rigor. **What We Offer** * Wellhub; * OnHappy; * Sesc; * Flexible Working Hours.