March 16
🏡 Remote – New York
• Developing data pipelines that effectively handle and process geo-spatial and event data, ensuring high-quality inputs for analyses and modeling • Building reliable, efficient, and scalable models for our ML capabilities • Evaluating the impact and effectiveness of models in production systems • Developing and implementing advanced machine learning algorithms to analyze driver behavior, predict potential risks, and enhance operational efficiency • Continuously exploring advancements in geo-spatial (and other) machine learning technologies and their potential applications in enhancing telemetry systems • Helping shape roadmaps by integrating business context and Data Science
• Bachelor’s or Master’s degree in Computer Science, Statistics, Applied Mathematics, or a related field • Minimum of 5 years of experience in machine learning, data science, or a related field • Demonstrated proficiency in commonly used machine learning frameworks and libraries • Solid experience in MLOps practices, including automation, monitoring, and maintaining machine learning models in production environments • Proven track record in developing advanced machine learning models, preferably with a specialization in handling and analyzing geo-spatial or “real-time” event data • Proficiency in using cloud computing platforms such as AWS, GCP, Azure, or similar for deploying and scaling machine learning models • Experience working with non-technical stakeholders to solve acute business problems
• Generous ownership package • Casual work environment • Diverse and inclusive culture • Electric atmosphere for professional development
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