**Location:** Hybrid – Central Office and Remote **Contract Type:** Permanent **Professional Challenge** Are you excited about advanced data analysis, developing predictive models, and contributing to the strategic growth of a leading organization in digital transformation? We are looking for a creative, curious, and rigorous individual with strong analytical and technical skills, capable of extracting valuable insights from large volumes of data. Your work will be pivotal in generating actionable insights to optimize decision-making, personalize products, and anticipate business trends within a dynamic and collaborative environment. **Key Responsibilities – Data Analysis, Machine Learning, and Business Intelligence** ------------------------------------------------------------------------------------------- * Design and implement statistical and machine learning models to solve complex problems and deliver value across various business areas. * Analyze, clean, and transform data from diverse sources to ensure its quality and suitability for analytical processes. * Visualize and communicate relevant findings through dashboards, clear reports, and effective presentations tailored for non-technical stakeholders. * Actively collaborate with engineering, business, marketing, and product teams to identify opportunities where data makes a difference. * Evaluate and apply data mining, predictive modeling, and statistical analysis techniques with a focus on delivering actionable outcomes. * Build prototypes, experiment with, and validate models using best practices in data science and quality control. * Ensure traceability, documentation, and reproducibility of analytical projects, contributing to the team’s collective knowledge. * Participate in the adoption and continuous improvement of emerging tools, methodologies, and technologies in data science. ### **Professional and Technical Requirements – Data Science, Statistics, and Predictive Modeling** * University degree in Statistics, Mathematics, Engineering, Computer Science, or related quantitative disciplines. * Minimum 3 years of proven experience as a Data Scientist or in similar roles focused on advanced analytics. * Solid foundation in statistics, mathematical modeling, and machine learning (supervised and unsupervised). * Proficiency in Python and associated libraries (pandas, scikit-learn, numpy, matplotlib, etc.) and/or R for data analysis and model prototyping. * Experience handling large volumes of data, writing SQL queries, and using relational and/or NoSQL databases. * Knowledge of modern data visualization and reporting techniques (Power BI, Tableau, Looker, or similar). * Ability to implement and deploy models in cloud environments (AWS, Azure, Google Cloud) and use version control systems such as Git. * Competence in data storytelling and rigorous validation methods for analytical results. * Intermediate-to-advanced English proficiency for documenting processes, conducting research, and collaborating with global teams. #### **Essential Tasks – Development, Validation, and Presentation of Analytical Solutions** * Identify, formulate, and translate business challenges into concrete, measurable data science projects. * Build, train, and optimize predictive, classification, and segmentation models that drive impact across operations and business outcomes. * Develop custom algorithms and validate their performance using testing, metrics, and statistical interpretation. * Synthesize complex results into actionable conclusions for both technical and non-technical audiences. * Collaborate on automating the analytical pipeline and integrating models into critical products or processes. * Promote continuous improvement through experimentation, review, and updating of models and data. ##### **Professional Profile – Collaboration, Innovation, and Analytical Thinking in Data Science** * A collaborative mindset, proactive attitude, and scientific curiosity to uncover hidden opportunities in data. * Outstanding communication skills and a positive attitude to contribute effectively within interdisciplinary and inclusive teams. * Critical thinking, strong ethical awareness, and high commitment to information quality, security, and privacy. * Ability to adapt to changing environments and continuously learn new tools and techniques. * Passion for excellence, diversity, and the real-world impact of data on people’s lives and businesses. ###### **Benefits – Career Development, Flexibility, and Excellence in Data Science** * Competitive compensation and performance-based variable pay schemes. * Access to continuous training, data science and artificial intelligence certifications, and international workshops. * Hybrid work environment with flexible working hours and remote work options based on project needs and individual requirements. * Participation in disruptive projects, innovation ecosystems, and real-world applied data science challenges. * Career development plans, internal mobility opportunities, and accelerated growth within a globally recognized company.