Data Scientist/Senior Data Scientist

Full time

Employment Information

Job levelMedium level

Salary$97 800 - $168 400

IndustryTechnology Information and Internet

Experience3+ years

LocationMenlo park, CA, United States

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Job Description

SLB’s Software Technology Innovation Center (STIC) is looking for an experienced data scientist with a solid fundamental understanding of various modern machine-learning methods to address highly challenging scientific and engineering problems. Drawing on an advanced degre in a quantitative field such as Computer Science, Physics, Statistics, or Applied Mathematics, the Data Scientist should demonstrate the knowledge and experience to tackle open-ended data problems by inventing new algorithms and technology. They will have advanced working knowledge and experience with Machine Learning (ML) algorithms and population-based meta-heuristic and gradient-based optimization methods. They will also research and assess next-generation technologies for data-driven modeling and optimization of complex systems. Additionally, the Data Scientist will collaborate with other scientists and engineers to leverage ML methods and algorithms for modeling and optimizing problems in the energy industry. They will participate in data science, industrial analytics, data-driven prognostics, data mining, and machine learning. Besides theoretical analysis and innovation, they will work closely with talented engineers to envision solutions and implement algorithms and models. Reporting to the Technical Lead, the position enjoys a highly visible role within the organization, with opportunities to collaborate closely with leading technology players in the Silicon Valley network. This is a very hands-on role, where the candidate will be expected to lead by owning solutions from inception to delivery.

Responsibilities

Research and develop data analytics and ML systems for business applications.
Work with subject matter experts to understand domain needs and constraints.
Work with software engineers to integrate ML solutions in business workflows.
Communicate complex 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.
Actively disseminate knowledge via Webinars, talks and tutorials for the technical community within SLB.
Strong knowledge of latest Generative AI technologies, preferably Large Language Models (LLMs), is highly recommended.
Apply theoretical knowledge to solve industrial problems.
Process large multivariate data sets collected from equipment operations, manufacturing tests, and diagnostic routines.
Communicate ideas, plans, and results effectively via oral and written reports.
Works across multiple cross-functional teams in high-visibility roles to prototype end-to-end data solutions.
Works effectively with peers, management, operations groups, and outside organizations.
Willingness to provide technical, social, and practical mentorship guidance to others as needed.
May participate in the relevant technical reviews and audits of the projects.
May review, mentor, and coach while defining and promoting the usage of standards, best practices, and lessons learned.

Qualifications

MS / Ph.D. in Computer Science, Mathematics, Applied Statistics, Physics, Engineering, or similar disciplines with demonstrated research capability, software experience or education, probability theory, decision theory, statistics, ML, reasoning, and inference frameworks.
At least 3-4 years of experience in a few areas: deep neural networks, reinforcement learning, Markov Random Fields, Bayesian networks, semi-supervised learning, natural language processing, computer vision, image processing, signal processing, distributed computing, and numerical optimization.
Software development skills and familiarity with database, programming, and data science development languages such as R, Python, TensorFlow, and PyTorch.
Familiarity with ML frameworks such as Tensorflow and PyTorch is a must.
Experience with big-data technologies like Hadoop/Spark or GCP-BigQuery is a plus.
Strong oral and written communication skills.

The anticipated salary range for this position is $97,800 - $168,400