Society of Exploration Geophysicists
Principal Data Scientist
Society of Exploration Geophysicists, San Francisco, California, United States, 94199
About the Company:LHH is seeking a Principal Data Scientist to join
our client's team
in San Francisco, CA (hybrid).We are looking for an experienced Principal Data Engineer 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. You will lead the effort in driving our data strategy, to enable the next generations of Machine Learning models to drive our Ad Business.Qualifications:Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.Minimum of 7 years of experience in data engineering with a focus on machine learning models, preferably in the AdTech industry.Minimum of 5 years of experience in programming languages such as Python, Scala, or Java.Extensive experience with big data technologies (e.g., Flink, Spark) and cloud platforms (e.g., GCP preferred, AWS).Minimum of 2 years of experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and experience with deployment of ML models at scale.Demonstrated ability to lead projects and collaborate effectively with cross-functional teams.Excellent problem-solving skills and ability to work in a fast-paced, dynamic environment.Previous Enterprise-level experience required.Responsibilities:Lead the design, implementation, and continuous improvement of data pipeline for machine learning that drive our AdTech platform.Collaborate with cross-functional teams to understand business needs and translate them into complex data models and algorithms.Manage the collection, storage, and processing of large-scale data sets to ensure they are optimized for machine learning.Develop and maintain a scalable and reliable data infrastructure that supports real-time and batch data processing.Stay abreast of industry trends and advancements in AdTech and machine learning to identify and implement best practices.Mentor senior data engineers and scientists, fostering a culture of technical excellence and innovation.Ensure data privacy and compliance standards are met in all data engineering and machine learning initiatives.
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our client's team
in San Francisco, CA (hybrid).We are looking for an experienced Principal Data Engineer 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. You will lead the effort in driving our data strategy, to enable the next generations of Machine Learning models to drive our Ad Business.Qualifications:Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.Minimum of 7 years of experience in data engineering with a focus on machine learning models, preferably in the AdTech industry.Minimum of 5 years of experience in programming languages such as Python, Scala, or Java.Extensive experience with big data technologies (e.g., Flink, Spark) and cloud platforms (e.g., GCP preferred, AWS).Minimum of 2 years of experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and experience with deployment of ML models at scale.Demonstrated ability to lead projects and collaborate effectively with cross-functional teams.Excellent problem-solving skills and ability to work in a fast-paced, dynamic environment.Previous Enterprise-level experience required.Responsibilities:Lead the design, implementation, and continuous improvement of data pipeline for machine learning that drive our AdTech platform.Collaborate with cross-functional teams to understand business needs and translate them into complex data models and algorithms.Manage the collection, storage, and processing of large-scale data sets to ensure they are optimized for machine learning.Develop and maintain a scalable and reliable data infrastructure that supports real-time and batch data processing.Stay abreast of industry trends and advancements in AdTech and machine learning to identify and implement best practices.Mentor senior data engineers and scientists, fostering a culture of technical excellence and innovation.Ensure data privacy and compliance standards are met in all data engineering and machine learning initiatives.
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