Senior Data Scientist, Blades Fleet Engineering

GE Vernova

1d•$113,200 - $188,800

About The Position

The Senior Data Scientist, Blade Fleet Engineering for GE Vernova, will lead proactive fleet performance management through advanced data science and machine learning. You will be responsible for driving sustained product improvement across the global fleet, shifting from reactive troubleshooting to a proactive, data-led reliability model. You will develop and implement scalable analytical initiatives and drive closed-loop lessons learned across the product lifecycle by leveraging large-scale industrial data.

Requirements

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 similar high-impact technical analytical role.

Nice To Haves

High proficiency in data analysis and visualization software (e.g., SQL, Python, R, MATLAB, PowerBI, or Tableau) with extensive experience interpreting large, complex datasets for technical decision-making.
In-depth experience in building, deploying, and monitoring production-grade machine learning models, with an understanding of how predictive maintenance applies to complex mechanical structures.
Strong foundation in statistical quality control (SQC), probabilistic modeling, and reliability engineering metrics (e.g., Weibull analysis, reliability growth modeling).
Experience developing data-driven action plans to mitigate fleet risks.
Familiarity with quality systems, procedure development, and technical execution.
Proven ability to communicate complex analytical findings and RCA outcomes to non-technical stakeholders.
Experience with Lean tools, coaching, and facilitating process improvement events (e.g., Kaizen).

Responsibilities

Leverage fleet-wide data across manufacturing, projects, and services platforms alongside AI-driven diagnostic tools to identify early-stage degradation patterns, enabling proactive maintenance strategies.
Develop and deploy machine learning algorithms to process large-scale historical failure data, accelerating root cause identification and validating the efficacy of corrective actions through rigorous statistical modeling.
Implement and maintain automated data visualization dashboards and pipelines to monitor fleet quality KPIs, ensuring real-time visibility into emerging trends for leadership and stakeholders.
Collaborate with performance and reliability teams to identify and address emerging technical issues through advanced predictive modeling before they impact fleet availability.
Drive continuous improvements in fleet data quality, data completeness, and the underlying data architecture supporting our analytics capabilities.
Facilitate data-driven "Kaizens" to achieve faster, more robust resolutions. Utilize statistical insights to own and support action items derived from Quality PSR (Problem Solving Report) countermeasures.
Drive the application of advanced data-centric problem-solving tools and methods throughout the root cause analysis process.
Collaborate with fleet performance management, manufacturing, projects, services, and digital technology teams to ensure a unified, data-driven approach to fleet reliability. Support data initiatives driven by cross-functional teams.

Benefits

medical, dental, vision, and prescription drug coverage
access to Health Coach from GE Vernova, a 24/7 nurse-based resource
access to the Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services
GE Vernova Retirement Savings Plan, a tax-advantaged 401(k) savings opportunity with company matching contributions and company retirement contributions, as well as access to Fidelity resources and financial planning consultants
tuition assistance
adoption assistance
paid parental leave
disability benefits
life insurance
12 paid holidays
permissive time off