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D&I Data Scientist

Job in Ahmadi, Kuwait
Listing for: SLB
Full Time position
Listed on 2026-03-09
Job specializations:
  • IT/Tech
    Data Scientist, Machine Learning/ ML Engineer
  • Engineering
Salary/Wage Range or Industry Benchmark: 30000 - 50000 KWD Yearly KWD 30000.00 50000.00 YEAR
Job Description & How to Apply Below

The Data Scientist is responsible for conducting undirected research and tackle open-ended data problems and questions. Drawing on an advanced degree in a quantitative field such as computer science, physics, statistics or applied mathematics, the Data Scientist demonstrates the knowledge to invent new algorithms to solve data problems.

  • 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.
Required

Skills & Qualifications
  • Programming:
    High proficiency in Python (specifically Pandas for data manipulation and Num Py for numerical computing).
  • Database Management:
    Ability to write SQL queries to extract data from relational databases.
  • Statistical Foundation:
    Understanding of probability, hypothesis testing, and statistical significance.
  • Machine Learning:
    Familiarity with ML libraries like Scikit-Learn.
  • Education:

    Currently pursuing or recently completed a degree (BS/MS) in Data Science, Statistics, Computer Science, Computer Engineering, Mathematics, or a related field.
Bonus
  • Basic exposure to LLMs or Prompt Engineering (e.g., using OpenAI or Lang Chain APIs).
  • Creating Dashboards and visualizations (ex. Power

    BI)
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