What you will do
- Apply data science methodologies to improve production, operations, and manufacturing processes.
- Develop and implement predictive models to enhance equipment reliability and reduce downtime.
- Analyze and optimize operational efficiency through data-driven insights.
- Develop, apply, and analyze physics-based or data-driven computational models.
- Utilize physics-based simulators to support operational decision-making.
- Collaborate with cross-functional teams to identify and solve complex operational problems.
- Communicate findings and recommendations to stakeholders through reports and presentations.
- Position could require 5-10% travel (domestic and/or international)
About You
Skills and Qualifications
- Bachelor's or Masters degree in Chemical Engineering, Chemistry, Mathematics, Computer Science, Civil, Electrical or Data Science from a recognized unviversity with GPA 7.0
- 3+ years of experience in a data science role, preferably in production, operations, or manufacturing environments.
- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Experience with physics-based simulators and computational modeling.
- Knowledge of predictive maintenance techniques and tools.
- Expertise in Computer Vision, Natural Language Processing (NLP), Time Series analysis.
- Experience with AI techniques and tools for operational improvements.
- Experience with software engineering practices, agile methodologies, DevOps, version control
- Experience working in Azure Databricks or any other data science frameworks
- Proficiency in programming languages such as Python.
- Software testing and development practices (Agile)
- Prior experience in operations, oil & gas, wells, or subsurface domain applications is highly desirable.
- Strong understanding of statistical analysis and data visualization tools (e.g., Tableau, Power BI).
Preferred Qualifications / Experience
- Ability to demonstrate initiative, teamwork, accuracy, effectiveness, and self-confidence
- Proven track record of developing and implementing data-driven solutions to improve operational efficiency.
- Strong problem-solving skills and the ability to work independently and as part of a team.
- Excellent communication skills, both written and verbal.