GE Vernova’s Blade Fleet Engineering team is seeking a Senior Data Scientist to lead proactive fleet performance management across the global blade fleet. In this role, you will apply advanced data science and machine learning to predictive analytics, automated quality reporting, and closed-loop reliability improvements, supporting better decisions for leadership and technical teams.
This position is based in Greenville, SC with an onsite work arrangement. The salary range for this role is USD 113,200 - 188,800 per year.
What you’ll do
- Use fleet-wide data from manufacturing, projects, and services platforms, together with AI-driven diagnostic tools, to spot early-stage degradation patterns and inform proactive maintenance strategies.
- Build and deploy machine learning algorithms that work with large-scale historical failure data to accelerate root cause identification and statistically validate the impact of corrective actions.
- Create and maintain automated data visualization dashboards and data pipelines to track fleet quality KPIs and provide near real-time visibility into emerging trends for leadership and stakeholders.
- Partner with performance and reliability teams to identify and address emerging technical issues through advanced predictive modeling before they affect fleet availability.
- Improve fleet data quality, data completeness, and the data architecture that underpins analytics capabilities.
- Lead data-driven Kaizens to support faster and more robust resolutions, using statistical insights to own and assist action items derived from Quality PSR (Problem Solving Report) countermeasures.
- Apply advanced data-centric problem-solving tools and methods throughout the root cause analysis workflow.
- Coordinate with fleet performance management, manufacturing, projects, services, and digital technology teams to maintain a unified, data-driven approach to fleet reliability, including support for cross-functional data initiatives.
Required qualifications
- Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative STEM field.
- 7+ years of professional experience in data science, predictive analytics, or a comparable high-impact technical analytical role.
- Strong proficiency with data analysis and visualization tools such as SQL, Python, R, MATLAB, PowerBI, or Tableau, including experience interpreting large, complex datasets for technical decision-making.
- Proven experience building, deploying, and monitoring production-grade machine learning models, with knowledge of how predictive maintenance applies to complex mechanical structures.
- Solid foundation in statistical quality control (SQC), probabilistic modeling, and reliability engineering metrics, including Weibull analysis and reliability growth modeling.
- Experience creating data-driven action plans to mitigate fleet risks.
- Familiarity with quality systems, procedure development, and technical execution.
- Demonstrated ability to communicate complex analytical findings and RCA outcomes to non-technical stakeholders.
- Experience using Lean tools to coach and facilitate process improvement events, including Kaizen.
Technologies
- SQL
- Python
- R
- MATLAB
- PowerBI
- Tableau
Benefits
- Medical, dental, vision, and prescription drug coverage
- Access to Health Coach from GE Vernova (24/7 nurse-based resource)
- Access to the Employee Assistance Program (24/7 confidential assessment, counseling and referral services)
- GE Vernova Retirement Savings Plan (tax-advantaged 401(k) with company matching contributions and company retirement contributions)
- Tuition assistance
- Adoption assistance
- Paid parental leave
- Disability benefits
- Life insurance
- 12 paid holidays
- Permissive time off
Relocation assistance: Yes