Leveraging data to drive insights and innovation in the transportation sector, enhancing operational efficiency and contributing to the company's strategic goals.
Requirements
- Possess a strong proficiency in Databricks, enabling the development and deployment of scalable data solutions.
- Demonstrate expertise in ML Ops, ensuring efficient model lifecycle management and operationalization.
- Have a deep understanding of artificial intelligence techniques and their applications in real-world scenarios.
- Exhibit domain knowledge in transportation and logistics, applying data science to solve industry-specific challenges.
Responsibilities
- Analyze complex datasets to extract actionable insights that drive business decisions in the transportation and logistics domain.
- Develop and implement machine learning models using Databricks to optimize logistics operations and improve service delivery.
- Collaborate with cross-functional teams to integrate AI solutions into existing systems, enhancing overall performance and efficiency.
- Utilize ML Ops practices to streamline the deployment and monitoring of machine learning models, ensuring scalability and reliability.
- Conduct research to identify emerging trends in artificial intelligence and their potential applications in transportation.
- Design and execute experiments to test hypotheses and validate model performance, ensuring robust and accurate outcomes.
- Provide technical guidance and support to team members, fostering a collaborative and innovative work environment.
Other
- 5 to 7 years of experience
- Experience in working within a hybrid work model, balancing remote and in-office collaboration effectively.
- Display excellent communication skills, capable of conveying complex technical concepts to diverse audiences.
- Hold a relevant degree in data science, computer science, or a related field, showcasing a solid educational foundation.
- Parsippany, NJ, USA (Hybrid – 3 days onsite)
