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Data Science Leader

2 months ago

San Francisco, California, United States Society of Exploration Geophysicists Full time
About the Company

The Society of Exploration Geophysicists is a leading organization in the field of geophysics, dedicated to advancing the science and application of geophysics. We are seeking a highly skilled and experienced Principal Data Scientist to join our team in a hybrid role.

Job Summary

We are looking for a seasoned Principal Data Scientist with a strong background in machine learning and a proven track record in the AdTech sector. The ideal candidate will lead our data engineering efforts, focusing on developing and optimizing our data pipelines for machine learning models to enhance our advertising technology solutions.

Key Responsibilities
  • Lead Data Engineering Efforts: Develop and implement data pipelines for machine learning models to drive our AdTech platform.
  • Collaborate with Cross-Functional Teams: Work with business stakeholders to understand needs and translate them into complex data models and algorithms.
  • Manage Large-Scale Data Sets: Ensure data is optimized for machine learning, and develop scalable and reliable data infrastructure.
  • Stay Up-to-Date with Industry Trends: Identify and implement best practices in AdTech and machine learning.
  • Mentor Senior Data Engineers and Scientists: Foster a culture of technical excellence and innovation.
  • Ensure Data Compliance: Meet data privacy and compliance standards in all data engineering and machine learning initiatives.
Requirements
  • Education: Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.
  • Experience: Minimum of 7 years of experience in data engineering with a focus on machine learning models, preferably in the AdTech industry.
  • Technical Skills: Extensive experience with big data technologies (e.g., Flink, Spark) and cloud platforms (e.g., GCP preferred, AWS).
  • Machine Learning Experience: Minimum of 2 years of experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and experience with deployment of ML models at scale.
  • Leadership Skills: Demonstrated ability to lead projects and collaborate effectively with cross-functional teams.