Job Description Summary

The Sr Staff Data Scientist is a senior technical leader who shapes and delivers high-impact Data Science and Machine Learning solutions for industrial operations across Oil & Gas Fossil Power and Renewable Power. You will lead small teams/programs set best practices for the end-to-end ML lifecycle and partner with business and engineering leaders to translate operational challenges into predictive and prescriptive solutions that drive measurable outcomes (reliability availability efficiency emissions cost). This role requires deep experience with time-series forecasting anomaly detection and predictive maintenance on large industrial datasets with Generative AI as a value-adding plus. Candidates must bring a minimum of 8 years experience in operations maintenance or monitoring of at least one of the above industry domains.

Job Description

Hybrid role: in office

Roles and Responsibilities

• Collaborate with business/domain leaders to identify prioritize and scope high-value ML use cases (e.g. time-series forecasting anomaly detection predictive maintenance) define success metrics and ensure measurable business impact.
• Lead and oversee the end-to-end DS/ML lifecycle: data acquisition cleaning feature engineering and exploratory analysis for industrial datasets (sensor/telemetry production logs emissions maintenance history).
• Develop validate and tune models across regression classification time-series (ARIMA/Prophet/LSTM/GRU/state-space) anomaly detection and ensembles; apply deep learning when appropriate; ensure robust cross-validation and reproducibility.
• Deploy models to production on cloud platforms (AWS/Azure/GCP); guide choices for model serving latency throughput and scalability; Own and influence the ML systems architecture including model lifecycle management feature pipelines CI/CD for ML observability drift detection and retraining strategies; partner with platform teams to define scalable and compliant ML-Ops patterns.
• Partner with data/platform engineering to operationalize pipelines and integrate models into business applications and workflows; ensure reliability observability and SLAs.
• Establish and champion standards reusable assets and best practices for data quality governance security-by-design and validation across programs.
• Mentor and coach data scientists/analysts; perform code/model reviews; grow skills and foster a strong data science culture; lead small teams/projects with moderate risk and complexity.
• Translate model outcomes into clear actionable insights for technical and non-technical stakeholders; communicate trade-offs risks and assumptions; quantify value realization.
• Collaborate with Reliability Engineering to apply reliability analytics (e.g. Weibull analysis survival/hazard models RGA/Crow-AMSAA) integrate CMMS/EAM/APM and historian/SCADA data and inform maintenance and spares strategies where applicable.
• Stay current with advancing ML methods (especially industrial IoT analytics streaming/real-time) and evaluate/pilot GenAI/LLM-assisted workflows (e.g. analytics automation documentation knowledge retrieval) as an added advantage.
• Contribute to functional data/analytics strategy and roadmaps; influence cross-functional ways of working; ensure alignment with GE Vernova standards and compliance requirements.

Education

• Bachelors Degree in Computer Science or STEM Majors (Science Technology Engineering and Math) with minimum 10 years of experience.
• Masters/PhD preferred.

Desired Characteristics

Technical Expertise:

• Expert proficiency in Python and SQL; strong in libraries such as Pandas NumPy scikit-learn; experience with TensorFlow/PyTorch where deep learning is applicable.
• Advanced time-series and anomaly detection for industrial data; predictive maintenance modeling and feature engineering for sensor/telemetry and maintenance data.
• Cloud ML platforms (e.g. AWS SageMaker Azure ML GCP Vertex AI) CI/CD for ML model registries monitoring and drift detection; design for scalable reliable serving.
• Data management practices at scale: data quality and cleansing strategies governance and security controls and fit-for-purpose data/feature architectures for ML.
• Real-time/streaming analytics and deployment considerations; integration into business applications and workflows.

Domain Knowledge:

• 15 Years of overall experience in Data Science and Analytics field with minimum 8 years experience in operations within at least one of: Oil & Gas Fossil Power Renewable Power; ability to translate operational realities (failure modes maintenance strategies process constraints) into features validation criteria and deployment constraints.
• Strong business understanding: align analytical solutions to P&L priorities and operational KPIs (availability MTBF/MTTR throughput energy yield emissions cost); articulate ROI and buy vs. build trade-offs; awareness of industry trends and regulatory context.

Leadership:

• Leads small teams/projects; attracts mentors and develops talent; establishes best practices and reusable patterns; builds trust and consensus across functions.
• Advanced problem solving: prioritizes removes roadblocks and aligns solutions to organizational objectives; introduces new perspectives to existing solutions.
• Consulting mindset: frames options and trade-offs provides risk-assessed recommendations and influences stakeholders to adopt data-driven decisions.
• Decision making & risk: makes informed decisions in ambiguous environments; balances performance latency and reliability trade-offs; promotes calculated risk-taking and learning.
• Change agent: plans and implements change programs drives adoption of new methods and platforms and partners with executives to realize value at scale.

Personal Attributes:

• Curiosity and creativity: connects ideas across domains; simplifies complex problems; champions progression from ideas to outcomes with speed.
• Comfort in ambiguity: delivers with incomplete information states assumptions clearly and course-corrects based on feedback; manages uncertainty for self and team.
• Strong written and verbal communication: crafts compelling narratives tailored to technical and non-technical audiences; coaches others on effective storytelling.

This role requires access to U.S. export-controlled information. If applicable final offers will be contingent on ability to obtain authorization for access to U.S. export-controlled information from the U.S. Government.

Additional Information

For candidates applying to a U.S. based position the pay range for this position is between $144800.00 and $217200.00. The Company pays a geographic differential of 110% 120% or 130% of salary in certain areas. The specific pay offered may be influenced by a variety of factors including the candidates experience education and skill set.

Bonus eligibility: discretionary annual bonus.

This posting is expected to remain open for at least seven days after it was posted on December 19 2025.

Available benefits include medical dental vision and prescription drug coverage; access to Health Coach from GE Vernova a 24/7 nurse-based resource; and access to the Employee Assistance Program providing 24/7 confidential assessment counseling and referral services. Retirement benefits include the 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. Other benefits include tuition assistance adoption assistance paid parental leave disability benefits life insurance 12 paid holidays and permissive time off.

GE Vernova Inc. or its affiliates (collectively or individually GE Vernova) sponsor certain employee benefit plans or programs GE Vernova reserves the right to terminate amend suspend replace or modify its benefit plans and programs at any time and for any reason in its sole discretion. No individual has a vested right to any benefit under a GE Vernova welfare benefit plan or program. This document does not create a contract of employment with any individual.