Petroleum Data Scientist providing predictive analytics and BI support for Oil and Gas company. Collaborating across departments to foster a data - driven culture and develop reporting tools.
About the role
- Senior Data Scientist developing and executing machine learning models for PG&E, focusing on risk mitigation and operational decision-making in safety and regulatory contexts.
Responsibilities
- Risk and regulatory modeling: Develop and maintain data pipelines and risk models that support RAMP/GRC regulatory filings .
- Program effectiveness analysis: Evaluate program effectiveness using statistical and causal-inference methods.
- Predictive modeling: Build and deploy predictive models for injury prediction and safety-related outcomes to support proactive risk mitigation and operational decision making.
- Model monitoring: Implement model monitoring for data drift, label shift, and model performance to ensure reliability of current and future predictive models.
- Cross-functional collaboration: Partner with safety, operations, and regulatory stakeholders to translate analytical insights into actionable recommendations; clearly communicate findings to technical and non-technical audiences.
Requirements
- Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
- 4 years in data science (or 2 years, if possess Master’s Degree as described above, or no experience, if possess Doctoral Degree or higher, as described above)
- Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience
- Proficiency in SQL and Python, including core libraries (NumPy, SciPy, pandas, scikit-learn, etc.).
- Master’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
- Experience with Git-based version control and modern software development workflows.
- Experience with natural language processing; exposure to large language models and prompt-engineering concepts a plus.
- Experience applying analytics in safety, compliance, or risk-related domains a plus.
Benefits
- Discretionary incentive compensation programs
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