Senior Data Scientist- AIQ

About AIQ

AIQ is a joint venture between ADNOC and Group 42, focused on developing artificial intelligence technologies for the oil and gas industry in the United Arab Emirates. AIQ develops and commercializes AI products and applications, providing end-to-end solutions by leveraging its data, cloud, and talent to reduce costs and generate revenue for clients. AIQ fosters an innovative and entrepreneurial spirit, providing opportunities to work with massive datasets, an AI infrastructure powered by the latest NVIDIA GPU cloud computing platform, and access to limitless computing, storage, and network resources.

• Develop next generation AI-enabled software products for oil & gas clients.
• Translate business objectives into actionable analyses and insights.
• Formalize Oil & Gas problems into AI problems.
• Contribute to the solution design, in collaboration with other data scientists, engineers and SMEs.
• Perform data preparation:
  Extract, clean, audit and preprocess data for analysis.
• Conduct Data QC:
  Analyze quality of data produced and proactively develop solutions to data quality issues.
• Contribute to the creation of large-scale labeled databases leveraging our annotation team.
• Develop data-driven algorithms and prototypes for classification, regression, anomaly detection, failure prediction and optimization.
• Evaluate proposed AI solutions with respect to the project objectives.
• Keep up to date with the latest technology trends.
• Apply state-of-the-art AI techniques to improve existing solutions.
• Deploy and maintain AI models in production.
• Help prepare and visualize interim and final results of analyses.
• Communicate ideas, plans, and results, effectively via oral presentations and written reports.

• Master’s degree or Ph.D. in Computer Science, Applied Mathematics, Statistics, or any AI-related field.
• Western education is mandatory.

• Very strong mathematical and analytical skills.
• Results-driven and proactive personality.
• Excellent communication skills.
• Ability to build AI models and to find impactful and actionable recommendations based on the model.
• Ability to manage ambiguity, take initiative, and hit the ground running.

• 3+ years of experience demonstrating depth and breadth in state-of-the-art machine-learning
  , deep-learning
  , computer-vision
  , natural language processing
  , signal processing
  , or other AI technologies.
• Relevant experience in industry or academia.
• Demonstrated experience in developing core AI algorithms in industry or for real-world problems.
• Demonstrated relevant experience in implementing robust and scalable industrial AI solutions.
• Experience in the oil & gas exploration & production company or oil field services company (e.g., Exxon Mobil, Chevron, Total, Shell, BP, Schlumberger, Halliburton, Baker Hughes) is a plus.

• Strong background in applied mathematics
  , algorithms and coding
  .
• Proficient in statistics
  , machine-learning or deep-learning
  .
• Strong background in AI application to computer-vision
  , NLP or signal-processing problems.
• Proficient in at least one development language (e.g.,
  Python
  ), one data analysis library (e.g.,
  Pandas
  ) and either a deep-learning framework (e.g.,
  Pytorch
  , Tensorflow
  ) or a machine-learning library (e.g.,
  Scikit-learn
  ).
• Theoretical and at least practical knowledge of popular machine-learning algorithms (
  PCA
  , Support Vector Machines
  , Random Forest
  , XGBoost
  , etc.) or deep-learning networks (
  RNNs
  , LSTMs
  , CNNs
  , shallow networks,
  GANs
  , Transformers
  , etc.).
• Hands-on with useful development tools (
  Py Charm ,
  Jupyter
  , Docker
  , Git
  , etc).
• Excellent communication, verbal and written skills.