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hackajob is partnering with Dunnhumby to fill this position. Create a profile to be automatically considered for this role—and others that match your experience.
· A relevant degree in a statistical, mathematical, or related discipline.
· Strong knowledge of statistical and mathematical methodologies, including forecasting, regression, linear models, time series analysis, hypothesis testing, and optimization.
· Proven ability to prototype solutions using Python and Spark, enabling development and testing of algorithms on large-scale datasets.
· Solid understanding of machine learning techniques and their applications in classification, prediction, and clustering.
· Expertise in experimental design methodologies to rigorously measure treatment effects.
· Proficiency in database technologies, including SQL and both relational and non-relational data models.
· Hands-on experience implementing algorithms at scale, such as ANCOVA, regularized linear models, clustering, random forests, and XGBoost.
· Ability to research and apply the latest machine learning approaches.
· Strong grasp of Object-Oriented Programming principles.
· Effective stakeholder management and communication skills.
· Capacity to quickly learn and utilize open-source statistical and machine learning libraries, including Pandas, SciPy, Scikit-learn, and TensorFlow.
· Experience developing solutions in areas such as Market Mix Modeling, Causal AI, and Generative AI.
hackajob is partnering with Dunnhumby to fill this position. Create a profile to be automatically considered for this role—and others that match your experience.