Data Scientist

Role purpose: Apply statistical, machine learning, and analytical methods to transform data into actionable insights that improve products, operations, and business decisions. Core responsibilities - Collect, clean, and validate structured and unstructured data from multiple sources. - Design, build, and evaluate predictive and descriptive models (e.g., classification, regression, clustering, forecasting). - Develop experiments and measurement frameworks (A/B testing, causal inference) to assess impact. - Create dashboards, reports, and clear narratives to communicate findings to technical and non-technical stakeholders. - Collaborate with engineering and product teams to deploy models and analytics into production workflows. - Monitor model performance, manage drift, and iterate on features and algorithms. - Document methodologies, ensure reproducibility, and support data governance and privacy standards. Required skills - Programming: Python or R; SQL for querying and data

manipulation. - Analytics: statistics, hypothesis testing, feature engineering, model evaluation. - Machine learning: supervised/unsupervised learning; model tuning and validation. - Data tools: notebooks, version control, and modern data stack concepts (ETL/ELT, warehouses). - Communication: ability to translate complex results into clear recommendations. Success outcomes - Deliver reliable insights and models that measurably improve key metrics. - Enable data-driven decision-making through scalable, well-documented solutions. Word de beste…