Inglês B2|C1
Responsibilities: Analyze large data volumes from various sources and generate actionable insights for different business areas (marketing, product, operations, etc.
).Develop and implement predictive models, machine learning algorithms, and statistical analysis techniques to solve business problems.Explore data of varying types and complexities, using analytical and visualization tools to identify trends and hidden patterns.Collaborate with teams from different areas, such as data engineering and business, to define requirements and analysis goals.Create clear, effective, and intuitive dashboards and reports to communicate findings and recommendations to stakeholders.Ensure the validation, interpretation, and alignment of models with business needs, proposing continuous optimizations and adjustments.Stay updated on the latest data analysis and machine learning methodologies, applying them to improve processes and outcomes.Work with different types of data (structured, semi-structured, and unstructured) across various analysis platforms (cloud and on-premise).Apply techniques such as data mining, time series analysis, clustering, regressions, and other statistical methods to extract value from data. Requirements: Proven experience as a Data Scientist, with at least 4 years in advanced data analysis and modeling.Strong skills in applied statistics and machine learning, with knowledge in areas such as regression, classification, clustering, decision trees, neural networks, among other techniques.Proficiency in Python and R, with experience using libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.Experience in data analysis and visualization using tools like Tableau, Power BI, or equivalents.Ability to work with relational databases (e.g., SQL) and NoSQL databases (e.g., MongoDB).Familiarity with Big Data platforms (Hadoop, Spark) and experience in cloud environments (e.g., AWS, Azure, Google Cloud).Ability to interpret complex data and provide clear, actionable business recommendations.Experience in creating prototypes and proofs of concept (PoC) for new models or analytical techniques.Capability to work independently and in teams, with strong communication skills to translate technical terms into accessible language for different stakeholders. Desired Competencies: Solid understanding of statistics and model validation methods, such as A/B testing, cross-validation, etc.Ability to solve complex problems using critical thinking and deep data analysis.Attention to detail, with a focus on quality, accuracy, and business impact.Knowledge of artificial intelligence and natural language processing (NLP) will be an advantage.
#J-18808-Ljbffr