Artificial Intelligence Specialist

• Collaborate with cross-functional teams, including engineers and domain experts, to drive data-driven improvements.
• Gather and preprocess data from various industrial sources, such as sensors, DCS systems, and manufacturing equipment’s.
• Analyze data to identify opportunities for process optimization, energy efficiency improvements, and cost reduction.
• Implement anomaly detection algorithms to identify abnormal patterns in industrial processes and equipment
• Develop predictive maintenance models to identify equipment failures and minimize downtime.
• Bring innovative ideas to apply image, video and audio analytics to reduce manual efforts like visual inspection/field monitoring of industrial plants.
• Create informative dashboards to communicate insights to operational teams and management.
• Deploy machine learning models into production systems for real-time monitoring and decision-making.
• Maintain documentation for data analysis processes, models, and findings.
• Ensure that data practices adhere to industry regulations and data privacy standards.
• Monitor and evaluate model performance and make necessary adjustments to maintain accuracy and reliability.

• You must hold a Bachelors/ Master’s degree in Engineering, Data science from a premier institute.
• You must have at least 5 years of experience in building data analytics-based products in industrial context, preferably in petroleum refineries.
• You possess the ability to identify business problems that can be addressed through data analysis and develop data-driven solutions (Engineering/Operational problems, computer vision-based products)
• Exceptional analytical and Problem-solving skills, with the ability to derive insights and opportunities from data are required.
• Understanding of the Oil & gas downstream domain to apply data science effectively is essential.
• Experience in developing AI/ML based Digital twins of industrial process/equipment’s.
• Experience in applying Optimization algorithms in line with AI/ML Models.
• Expertise in Python for data manipulation, analysis, and modeling. Familiarity with popular libraries such as NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn etc.
• Proficiency in deep learning tools keras, TensorFlow, pytorch, cafee, etc.
• Proficiency in developing, evaluation and selecting the best ML model based on the problem under consideration with an Engineering sense.
• You must also be able to bring ideas from conceptualization to productionizing
• Proficiency in visualization tools and packages; and in communicating data science topics to non-technical audience
• Basic project management skills to plan, execute, and deliver data science projects on time and within scope is preferred.

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