Key Responsibilities:
Lead multidisciplinary teams to deliver digital and AI-driven projects for Gas Plants from solution scouting to value realization.

Conduct feasibility studies to identify use cases for advanced analytics to solve technical problems, optimize operations, or improve safety and revenue.

Analyze business problems and determine the relevant machine learning task (classification, clustering, regression, forecasting, etc.).

Select and apply appropriate ML algorithms including Decision Trees, SVM, kNN, Neural Networks, and Deep Learning models.

Develop and deploy predictive models using techniques such as linear, logistic, and dynamic regression.

Minimum Requirements:
Education:

Bachelor’s degree in Chemical Engineering, Mechanical Engineering, Electrical Engineering, Computer Engineering, or Computer Science from an accredited university.

Advanced degree with specialization in AI, ML, applied statistics, or operations research is highly desirable.

Required Experience:
Expertise in: Statistics, Machine Learning, Time Series, Deep Learning, NLP, and Foundation Models.

Strong hands-on experience with Python and machine learning libraries.

Experience in:

Algorithm selection, model development, forecasting, and deployment.

Implementing ML solutions in upstream/downstream oil & gas operations.

Working with automation systems, OPC, PI systems, and real-time data platforms.

Identifying business use cases and delivering digital solutions within cross-functional teams.

Knowledge of Digital Transformation initiatives is an asset.

Preferred Skills:
Programming: Python, Java, C

Technologies/Tools: Scikit-learn, NLTK, SpaCy, Gensim, SciPy, TensorFlow, Keras, Pandas, PyTorch, Hugging Face, LangChain, Ollama, IBM watsonx, Watson Discovery, Elastic, Milvus, FAISS, Streamlit, FastAPI, ArcGIS

Please send your resume/CV