Head of Data Science
August 10
🔄 Hybrid – San Francisco
Description
• Solve complex, real-world problems that directly impact the agriculture industry and beyond. • Actively participate in hands-on technical work, including Modeling, developing, and deploying ML solutions. • Lead the end-to-end lifecycle from concept to production of critical predictive services and products. • Develop and implement a robust data science roadmap in cooperation with product management. • Provide ongoing insights and improvements in data quality. • Leverage ML solutions to enhance the quality and value of sensor data streams. • Build and manage a high-performing data science team. • Report to the CEO and work closely across the management team to optimize organizational collaboration.
Requirements
• Proven track record of continuous development and staying current in a rapidly changing field. • Strong experience and interest in growing and leading teams. • Proven ability to balance hands-on technical work with leadership responsibilities. • Practical experience with Machine Learning methods and common cloud-based data analysis tools and frameworks (Hadoop, Redshift, SageMaker, Spark, SQL, R, etc.). • Extensive experience with Machine Learning development in Python. • Experience with modern Machine Learning frameworks such as TensorFlow or Torch. • Experience with Machine Learning cloud services on Google, AWS, or Azure. • Practical understanding of building, cleaning, and operationalizing data sets. • Strong mathematical and statistical background. • Domain knowledge of agronomics, plant biology, weather, environmental, and spatial data is a plus. • Experience with startups is a plus. • Ability to achieve operational excellence by instilling a data-driven mentality across the organization. • Developing operational metrics and KPIs that are meaningful to the business and ensure successful outcomes. • Advanced Degree in Agronomy, Computer Science, Applied Mathematics, Statistics, or another scientific field.
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