Job description

Job Description Summary As an entry-level Data Scientist, you will work with engineers, data professionals and product teams to frame problems, prepare data, build and evaluate analytical or machine-learning models, and communicate results. You will contribute to practical solutions that are technically rigorous, understandable and ready to be used by the business. This role is designed for a recent graduate who brings strong fundamentals, curiosity and evidence of applied project work. Job Description What You Will Do Partner with engineering and business stakeholders to translate a question into a clear analytical problem, success criteria and testable approach. Explore, clean, join and validate structured and unstructured datasets; document assumptions, limitations and data-quality issues. Build baseline and advanced models using statistical analysis, machine learning, optimization or time-series methods as appropriate. Compare models using relevant performance metrics and evaluate uncertainty, bias, robustness and generalization. Create clear visualizations, notebooks and concise presentations that explain methods, findings and recommended actions. Work with Data Engineers and AI Engineers to move useful analyses from prototypes toward reusable, monitored solutions. Use version control, code review, testing and reproducible workflows to create maintainable analytical assets. Protect confidential information and follow cybersecurity, data governance, intellectual property and Responsible AI requirements. Continue developing domain knowledge in energy, engineering and industrial systems through hands-on work and mentorship. Required Qualifications Bachelor s degree completed by the start date in Data Science, Statistics, Mathematics, Computer Science, Engineering, Operations Research, Physics or a related quantitative field. Foundational knowledge of statistics, probability, experimental design and machine-learning concepts. Hands-on experience with Python or R through coursework, research, internships, co-ops or independent projects. Experience using common data analysis and visualization tools such as pandas, NumPy, scikit-learn, SQL, Jupyter, matplotlib, seaborn, Power BI or equivalents. Ability to explain technical work clearly in writing and conversation to both technical and non-technical audiences. Demonstrated problem-solving, collaboration, attention to detail and willingness to learn. Preferred Qualifications Internship, co-op, research, capstone or portfolio experience applying analytics or machine learning to a real problem. Exposure to cloud data platforms, distributed computing, data pipelines, Git, containers or ML lifecycle tools. Experience with time-series, simulation, optimization, computer vision, natural language processing or generative AI. Interest in renewable energy, physical systems, manufacturing or engineering applications. Experience validating results with subject-matter experts and incorporating feedback into an improved solution. GE Vernova offers a great work environment, professional development, challenging careers, and competitive compensation. GE Vernova is an Equal Opportunity Employer . Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law. GE Vernova will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable). Relocation Assistance Provided: Yes For candidates applying to a U.S. based position, the pay range for this position is between $70,400.00 and $105,600.00. 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 candidate’s 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 September 10, 2026. 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.

Requirements

Must-haves

Job Description What You Will Do Partner with engineering and business stakeholders to translate a question into a clear analytical problem, success criteria and testable approach.
Explore, clean, join and validate structured and unstructured datasets; document assumptions, limitations and data-quality issues.
Build baseline and advanced models using statistical analysis, machine learning, optimization or time-series methods as appropriate.
Compare models using relevant performance metrics and evaluate uncertainty, bias, robustness and generalization.
Create clear visualizations, notebooks and concise presentations that explain methods, findings and recommended actions.
Work with Data Engineers and AI Engineers to move useful analyses from prototypes toward reusable, monitored solutions.
Use version control, code review, testing and reproducible workflows to create maintainable analytical assets.
Protect confidential information and follow cybersecurity, data governance, intellectual property and Responsible AI requirements.
Continue developing domain knowledge in energy, engineering and industrial systems through hands-on work and mentorship.
Required Qualifications Bachelor s degree completed by the start date in Data Science, Statistics, Mathematics, Computer Science, Engineering, Operations Research, Physics or a related quantitative field.
Foundational knowledge of statistics, probability, experimental design and machine-learning concepts.
Hands-on experience with Python or R through coursework, research, internships, co-ops or independent projects.
Experience using common data analysis and visualization tools such as pandas, NumPy, scikit-learn, SQL, Jupyter, matplotlib, seaborn, Power BI or equivalents.
Ability to explain technical work clearly in writing and conversation to both technical and non-technical audiences.
Demonstrated problem-solving, collaboration, attention to detail and willingness to learn.
Exposure to cloud data platforms, distributed computing, data pipelines, Git, containers or ML lifecycle tools.
Experience with time-series, simulation, optimization, computer vision, natural language processing or generative AI.
Interest in renewable energy, physical systems, manufacturing or engineering applications.
Experience validating results with subject-matter experts and incorporating feedback into an improved solution.
GE Vernova will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).
Relocation Assistance Provided: Yes
This posting is expected to remain open for at least seven days after it was posted on September 10, 2026.

Nice-to-haves

Preferred Qualifications Internship, co-op, research, capstone or portfolio experience applying analytics or machine learning to a real problem.

Application prep

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Keywords to mirror

machine learningaipythonsqlml

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Parental Leave

Professional Development