Sr Data Scientist

Job Description

A role with Target Data Science & Engineering means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Whether you join our Statistics, Optimization or Machine Learning teams, you ll be challenged to harness Target s impressive data breadth to build the algorithms that power solutions our partners in in Marketing, Supply Chain Optimization, Network Security and Personalization rely on. Position Overview : Develop a strong understanding of business and operational processes. Analyse large datasets to derive insights for business process improvements and solution development. Develop optimization-based solutions, mathematical models (probabilistic/deterministic models), predictive models, and implement them in real-world production systems with measurable impact. Add new capabilities and features to the simulation framework to reflect the complexities of an evolving supply chain network. Develop and deploy modules to run simulations for testing and validating multiple scenarios to evaluate the impact of various inventory purchasing and management strategies. Enhance and maintain the simulation environment to enable testing/deploying new features for running custom scenarios. Coordinate the analysis, troubleshooting, and resolution of issues in models and software. About You: Bachelors/MS/PhD in Mathematics, Statistics, Operations Research, Industrial Engineering, Physics, Computer Science, or related fields. 4+ years of relevant experience. Experience in applying Operations Research to solve complex problems in Supply chain or related domain. Strong analytical thinking and data visualization skills. Ability to creatively solve business problems and innovate new approaches. Experience cleaning, transforming, and analysing large datasets for insights leading to business improvements. Proficiency in Python, SQL, Hadoop/Hive, Spark. Strong experience in JVM-based languages like Java or Kotlin preferred. Knowledge of mathematical and statistical concepts, optimization, data structures, algorithms, data analysis, simulations, and visualizations applied to business problems. Good working knowledge of machine learning, probability estimation methods, linear programming (integer, real, and mixed integer), stochastic processes, and their applications.