| Duties: | Responsible for the exploration, aggregation, transformation, and cleansing of vehicle data across a variety of disparate sources and platforms, ensuring data integrity and consistency at scale; design, implement, and continuously optimize advanced predictive machine learning models to drive accurate and actionable business forecasts, leveraging complex datasets; architect, develop, and maintain high-performance APIs in Python, ensuring seamless integration with diverse data ecosystems while adhering to best practices for scalability and security; support efforts to streamline and automate the data pipeline, encompassing data acquisition, feature engineering, model development, and deployment workflows, optimizing for performance, efficiency, and scalability; coordinate and execute complex ad-hoc data analysis tasks, providing rapid, data-driven insights for immediate business needs; provide mission-critical on-call support to ensure the continued operation of business production systems, troubleshooting and resolving issues with minimal impact to operations; utilize and apply knowledge of Python, SQL, Scikit-learn, XGBoost, Prophet, ARIMA, RESTful APIs, GCP, Terraform, Docker, VBA, and ODBC to complete assignments; translate complex analytical findings into clear, actionable insights; utilize cutting-edge Natural Language Processing (NLP) techniques to extract valuable insights from large volumes of unstructured text data, integrating AI-driven solutions to deliver sophisticated data analysis that directly impacts automotive operations and strategic initiatives; apply advanced statistical methodologies including Regression Analysis, Bayesian Inference, and machine learning-based forecasting techniques, to model and predict complex variables like market incentives, inventory management, sales forecasting, and operational performance; provide data-driven insights to optimize production strategies and facilitate high-level decision-making; leverage Cloud Computing platforms (primarily GCP) to architect and scale infrastructure for processing, storing, and analyzing massive automotive datasets; deploy data science solutions that integrate seamlessly with manufacturing and operational environments to drive efficiency, accuracy, and business intelligence; and present models and results to stakeholders, including business executives, to influence strategic decision-making. Education: Master’s – Data Science, Computer Science, Computer Engineering, Systems Engineering, or in a related field of study (will accept equivalent foreign degree); Training: None; Experience: One (1) year in the position above, as a Data Analyst, Data Engineer, as a Data Engineering Specialist, or in a related occupation; Other Requirements: Experience must include one (1) year use of all the following: Python, SQL, Scikit-learn, XGBoost, Prophet, ARIMA, RESTful APIs, GCP, Terraform, Docker, VBA, and ODBC. |