D&I Data Scientist

Slb NV
Houston, TX, United States
5 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Agile Methodology Artificial Neural Networks Data Integration DevOps Python (Programming Language) Machine Learning NumPy Tensorflow Software Engineering Explainable AI (XAI) Cloud Platform System
+10 more
Pytorch Large Language Models Deep Learning Keras Pandas Scikit Learn Information Technology Data Analytics Machine Learning Operations Software Version Control

Job description

  • Research and assess next-generation technologies for machinery diagnostics and prognostics and data-driven modeling and optimization of complex systems.
  • Demonstrate advanced working knowledge and experience with machine learning algorithms and population-based meta-heuristic optimization methods.
  • Generate innovative ideas, establish new research directions, and shape and execute on technical projects.
  • Maintain state-of-the-art knowledge and contribute to technical discussions and reviews as an expert in related areas of responsibility.
  • Apply theoretical knowledge to solve industrial problems.
  • Process large multivariate data sets collected from equipment operations, manufacturing tests and diagnostic routines.
  • Apply engineering knowledge in developing data-driven algorithms for anomaly detection, failure prediction and optimization.
  • Communicate ideas, plans and results effectively via oral and written reports.
  • Collaborate with field and product engineers to identify key health monitoring parameters of a system.

Requirements

Data Science, Data Science, Earth Sciences, Statistics, Computer Science, Mathematics, Algorithms, Physics, Problem Solving Skills, Data Modeling, * Knowledge and practical experience in statistical analysis techniques (e.g., classification, regression, time-series, Bayesian techniques) and machine learning techniques (e.g., decision trees, ensemble methods, deep learning, neural networks, validation methods).

  • Practical experience in the machine learning lifecycle, from problem formulation and data acquisition to model building and deployment at enterprise scale.
  • Conceptual and mathematical understanding of algorithms, models, model assessment techniques, solution development and explainable AI.
  • Knowledge and experience in code design, testing, and ML Ops practices.
  • Specialization in at least one sub-domain, such as time series forecasting, Bayesian skills or NLP-GenAI.
  • Proficiency in Python, including packages such as NumPy, pandas, scikit-learn, Keras, TensorFlow, and PyTorch.
  • Experience with software engineering practices, agile methodologies, DevOps, and version control.
  • Experience in Data and Cloud environments along with APIs and data integration
  • Experience with GenAI/LLMs

Benefits & conditions

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International Opportunities

Global adventure, broad exposure, and limitless learning await you. Youβ€™β€˜ll be part of the most multi-cultural and diverse team of experts in any industry, anywhere.

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Insurance

Health, vision, and dental insurance for you and your dependents available from day one.

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Learning Opportunities

Global adventure, broad exposure, and limitless learning await you. Youβ€™β€˜ll be part of the most multi-cultural and diverse team of experts in any industry, anywhere.

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Diverse and Inclusive

Our exceptional and diverse people are the pulse and spirit of who we are. Every day, you will enrich your knowledge in an environment where differences in thought, creativity and experiences are embraced.

About the company

We are a global technology company, driving energy innovation for a balanced planet. Together, we create amazing technology that unlocks access to energy for the benefit of all.

Global in outlook, local in practice - and with a united, shared passion for discovering solutions, we hire talented, driven people and support them to succeed, personally and professionally.

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