Principal Data Scientist

About the Role

Key Responsibilities

• Lead the ideation, prototyping, and implementation of cutting-edge AI/ML solutions to meet emerging business requirements in the oil and gas industry.
• Design, develop, and implement end-to-end machine learning pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment, specifically tailored for industrial analytics.
• Develop, train, and optimize deep learning models using neural network architectures (e.g., CNNs, RNNs, Transformers, GANs) and frameworks such as TensorFlow, Keras, or PyTorch, applying these models to solve complex problems in computer vision, asset health monitoring, predictive maintenance, and operational optimization.
• Develop and deploy robust models for assessing and predicting the health of oil and gas assets, integrating first principle and physics-informed approaches with data-driven models.
• Apply advanced statistical analysis techniques to identify patterns, quantify uncertainties, and support data-driven decision-making.
• Architect, develop, and deploy scalable machine learning solutions utilizing Azure Databricks and other Azure cloud services for big data and ML solutions.
• Collaborate with data architects, data engineers, and software developers to ensure effective data collection, processing, and storage.
• Perform comprehensive exploratory data analysis to identify patterns, generate insights, and communicate findings to stakeholders.
• Optimize model performance by addressing issues such as overfitting, underfitting, and bias, ensuring scalability and performance in production environments.
• Mentor junior data scientists and ML engineers in model development, data handling, and ethical considerations in AI/ML practices.
• Stay abreast of the latest advancements in machine learning, AI research, and computer vision techniques, actively applying new methods to enhance model performance and scalability.

Requirements

• Master's or Ph.D. in Computer Science, Chemical Engineering, Statistics, Mathematics, or a related field with 7+ years of relevant experience.
• Expertise in Python and proficiency in machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Proven experience with cloud platforms, specifically Azure, including Azure Databricks.
• Hands-on experience in applying deep learning techniques and neural networks to industrial analytics and computer vision problems.
• Demonstrated domain knowledge within the Oil & Gas industry, including understanding of operational data and industry-specific challenges.
• Strong problem-solving, critical thinking, and analytical skills, with experience in relational and non-relational databases, time-series data, and data visualization.
• Experience in asset health modeling, first principle modeling, physics-informed modeling, and advanced statistical analysis.
• Excellent verbal and written communication skills, capable of conveying complex technical concepts to non-technical stakeholders.
• Ability to work collaboratively within diverse teams and contribute to an inclusive work environment.
• A passion for continuous learning and applying new AI/ML and computer vision technologies to real-world problems.

Nice to Have

• Experience with multimodal modeling in an industrial context.
• Familiarity with deploying scalable AI solutions in cloud environments beyond Azure.
• Experience mentoring or leading teams of data scientists or ML engineers.

Qualifications

• 7+ years of relevant experience in AI/ML and computer vision.
• Master's or Ph.D. in a related technical field.

Benefits & Perks

• Comprehensive benefits package including medical, dental, vision, life, and disability insurance.
• Employee stock purchase program (ESPP) and 401K with company match.
• Health Savings Account (HSA) and Employee Assistance Program (EAP).
• Professional development resources including on-demand training, certification prep, and technical courses.
• Access to discounts and perks, including certifications and memberships.
• Support from dedicated customer service teams and certified career coaching.