Job description

Responsibilities

  • Utilize machine learning and AI techniques to analyze logistics data, focusing on warehouse and transportation metrics.
  • Develop algorithms and models to parse and process large volumes of active incoming field data.
  • Implement systems to ingest data from MongoDB, AWS Time Stream DB, and/or Redis DB during the backend ingestion process.
  • Design and execute machine learning strategies, including Deep Q learning, to improve process efficiency in logistics operations.
  • Collaborate with cross-functional teams to identify opportunities for process improvement and implement data-driven solutions.
  • Stay updated with the latest advancements in machine learning, AI, and related fields to enhance analytical capabilities.

Requirements

  • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.
  • Strong proficiency in algorithms, data structures, and machine learning techniques.
  • Prior experience in performing data analysis and machine learning on logistics data is highly desirable.
  • Proficiency in programming languages such as Python, Java, or C++.
  • Experience with data storage systems like MongoDB, AWS Time Stream DB, and Redis DB.
  • Excellent problem-solving skills and ability to work with large datasets.
  • Strong communication and collaboration skills to work effectively in a team environment.

Additional Skills (Preferred)

  • Familiarity with Deep Q learning and other advanced machine learning strategies.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud.
  • Knowledge of software development methodologies and practices.

This job was posted by Alisha from Refactor Academy.

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