SLB
Overview
Data Scientist role at SLB. Location: Software Technology Innovation Center (STIC), Menlo Park, CA, USA. We are seeking scientists and engineers with a strong fundamental understanding of various modern data-driven methods to address highly challenging scientific and engineering problems in applications of Artificial Intelligence, Optimization, and Data Science to industrial problems in the Energy sector. The candidate is responsible for conducting undirected technology development and tackling open-ended AI/ML problems. The ideal candidate has an advanced degree in a quantitative field and demonstrates the ability to invent new algorithms to solve data problems. The candidate participates in data science, artificial intelligence, machine learning, and industrial analytics, with emphasis on modern deep learning methods, foundation models, and generative AI solutions. Responsibilities
Work with product champions, product managers, and designs to engineer the appropriate computer system solution for SLB. Communicate sophisticated ML concepts to management, clients, and the business community. Research and assess next-generation technologies for inference, predictive modeling, general-purpose data-driven modeling, and optimization of complex systems. Demonstrate advanced working knowledge and experience with data analytics, machine learning algorithms, and optimization methods. Generate innovative ideas, establish new technology development directions, and shape and execute technical projects. Maintain state-of-the-art knowledge and contribute to technical discussions and reviews as an expert in related areas of responsibility. Communicate ideas, plans, and results effectively via oral and written reports. Work with peers, management, operations groups, and outside organizations. May participate in relevant technical reviews and audits of projects. Review, mentor, and coach junior team members while defining and promoting standards, best practices, and lessons learned. Work across multiple cross-functional teams in high-visibility roles to prototype end-to-end data solutions. Minimum Technical and Experience Requirements
1-5 years of experience in applied technology development, applied research of deep learning in physical-systems, or a combination of both. Experience in data-driven modeling using modern data science techniques from statistics and machine learning. Ability to prototype cutting-edge research models (foundation models and GenAI) and assess their applicability to SLB domain challenges. Hands-on experience in modern machine learning frameworks such as TensorFlow and PyTorch, with emphasis on full computer system design. Expertise with one or more AI, Data Science or Machine Learning solution suites from major cloud providers. Programming skills for early-stage prototyping and development toward production in modern stacks (cloud, containers, etc.). Advanced ability to work with data-driven models, including parameter tuning, feature engineering, and related tasks. Experience in robust model development aligned with business and engineering requirements. PhD or Masters degree in a Scientific or Engineering discipline with strong emphasis on mathematics fundamentals of Data Science and AI. Engineering training at the undergraduate level is a plus. Team-oriented behaviors and the ability to take technology and scientific risks to explore non-traditional approaches and guide others. Strong written and verbal communication skills. Ability to convey advanced data science and AI concepts to audiences with diverse backgrounds. Proficiency in programming languages such as Python, R, or others related to modern data-driven products for IoT/Edge. Compensation and benefits are listed in compliance with applicable law. The anticipated annual salary range for this position is $140,000 - $212,000 for candidates hired onto a local United States payroll.
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Data Scientist role at SLB. Location: Software Technology Innovation Center (STIC), Menlo Park, CA, USA. We are seeking scientists and engineers with a strong fundamental understanding of various modern data-driven methods to address highly challenging scientific and engineering problems in applications of Artificial Intelligence, Optimization, and Data Science to industrial problems in the Energy sector. The candidate is responsible for conducting undirected technology development and tackling open-ended AI/ML problems. The ideal candidate has an advanced degree in a quantitative field and demonstrates the ability to invent new algorithms to solve data problems. The candidate participates in data science, artificial intelligence, machine learning, and industrial analytics, with emphasis on modern deep learning methods, foundation models, and generative AI solutions. Responsibilities
Work with product champions, product managers, and designs to engineer the appropriate computer system solution for SLB. Communicate sophisticated ML concepts to management, clients, and the business community. Research and assess next-generation technologies for inference, predictive modeling, general-purpose data-driven modeling, and optimization of complex systems. Demonstrate advanced working knowledge and experience with data analytics, machine learning algorithms, and optimization methods. Generate innovative ideas, establish new technology development directions, and shape and execute technical projects. Maintain state-of-the-art knowledge and contribute to technical discussions and reviews as an expert in related areas of responsibility. Communicate ideas, plans, and results effectively via oral and written reports. Work with peers, management, operations groups, and outside organizations. May participate in relevant technical reviews and audits of projects. Review, mentor, and coach junior team members while defining and promoting standards, best practices, and lessons learned. Work across multiple cross-functional teams in high-visibility roles to prototype end-to-end data solutions. Minimum Technical and Experience Requirements
1-5 years of experience in applied technology development, applied research of deep learning in physical-systems, or a combination of both. Experience in data-driven modeling using modern data science techniques from statistics and machine learning. Ability to prototype cutting-edge research models (foundation models and GenAI) and assess their applicability to SLB domain challenges. Hands-on experience in modern machine learning frameworks such as TensorFlow and PyTorch, with emphasis on full computer system design. Expertise with one or more AI, Data Science or Machine Learning solution suites from major cloud providers. Programming skills for early-stage prototyping and development toward production in modern stacks (cloud, containers, etc.). Advanced ability to work with data-driven models, including parameter tuning, feature engineering, and related tasks. Experience in robust model development aligned with business and engineering requirements. PhD or Masters degree in a Scientific or Engineering discipline with strong emphasis on mathematics fundamentals of Data Science and AI. Engineering training at the undergraduate level is a plus. Team-oriented behaviors and the ability to take technology and scientific risks to explore non-traditional approaches and guide others. Strong written and verbal communication skills. Ability to convey advanced data science and AI concepts to audiences with diverse backgrounds. Proficiency in programming languages such as Python, R, or others related to modern data-driven products for IoT/Edge. Compensation and benefits are listed in compliance with applicable law. The anticipated annual salary range for this position is $140,000 - $212,000 for candidates hired onto a local United States payroll.
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