ILI Data Analyst
Pipesurvey International USA
Greater HoustonFresher3h agovia LinkedIn
This job at a glance
- Who can apply
- New grads, no experience needed · Bachelor's degree
- Must know
- Data analysisStatisticsOperationsStakeholder managementPythonR
- Work
- On-site in Greater Houston
- Pay
- Not stated by the employer.
- Listed
- Nov 11, 2026 · still open
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About the Role
The ILI Data Analyst is a full-time, on-site role responsible for interpreting and validating ultra-high-resolution in-line inspection data.
Key Responsibilities
- Processing raw inspection data.
- Performing quality checks on inspection data.
- Applying statistical and analytical techniques to identify anomalies, corrosion, and other integrity threats.
- Creating clear reports and visualizations for pipeline operators.
- Collaborating with engineering and operations teams to refine data models and workflows.
- Supporting continuous improvement of analysis tools and methodologies.
- Documenting analysis procedures.
- Maintaining data consistency and traceability.
- Communicating findings and recommendations in a clear, concise manner to internal stakeholders and clients.
Requirements & Tech Stack
- Strong analytical skills.
- Hands-on experience with data analytics tools and techniques.
- Proficiency in statistics for data validation, trend analysis, and anomaly detection.
- Experience with data modeling, including structuring large datasets and building models to support integrity assessments.
- Effective communication skills, with the ability to explain complex technical findings to non-technical audiences.
- Proficiency with common data analysis software (e.g., Python, R, SQL, or similar) and spreadsheet tools.
- Attention to detail.
- Commitment to data quality.
- Ability to work collaboratively in an on-site team setting.
Qualifications
- Bachelor’s degree in engineering, data science, mathematics, statistics, or a related field, or equivalent practical experience.
- Experience in pipeline integrity, oil and gas, or industrial inspection environments is beneficial.