Skills Required: Must have experience with: SQL and big-data tooling for mining and transforming high-volume logistics datasets; Python for production-grade data science; Time-series forecasting; MLOps and product ionization, including feature pipelines, model monitoring, Airflow-style orchestration, and reliability; Experimentation and causal inference (A/B tests and uplift modeling) to translate business needs into measurable DS solutions; Applying machine learning (supervised or unsupervised models) to improve efficiency, cost, and experience; Large-scale algorithm development and testing, including design, A/B evaluation, and KPI alignment; Cross-functional communication and stakeholder management with product/engineering/ops; Tableau dashboarding and BI visualization, including building executive dashboards, operational reporting, and self-service analytics; Business intelligence, including data warehousing, ETL, KPI frameworks, and integration with tools such as Tableau; Executive presentation and storytelling. Minimum education and experience required: Master’s degree or the equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field plus 1 year of experience in an analytics related field; OR Bachelor’s degree or the equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field plus 3 years of experience in an analytics related field.