
GE Vernova Data Scientist
Greenville, SCFull-time$70–106K/yrSeen todaySeen in employer's feed today
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At a glance
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Job overview
As an entry-level Data Scientist, the role works with engineers, data professionals, and product teams to frame problems, prepare data, build and evaluate analytical or machine-learning models, and communicate results. It is designed for a recent graduate with strong fundamentals, curiosity, and applied project work, contributing practical solutions that are technically rigorous, understandable, and ready for business use.
Skills & qualifications
Skills
Qualifications
Benefits
Full 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
Key Responsibilities
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Partner with engineering and business stakeholders to translate a question into a clear analytical problem, success criteria and testable approach.
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Explore, clean, join and validate structured and unstructured datasets; document assumptions, limitations and data-quality issues.
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Build baseline and advanced models using statistical analysis, machine learning, optimization or time-series methods as appropriate.
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Compare models using relevant performance metrics and evaluate uncertainty, bias, robustness and generalization.
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Create clear visualizations, notebooks and concise presentations that explain methods, findings and recommended actions.
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Work with Data Engineers and AI Engineers to move useful analyses from prototypes toward reusable, monitored solutions.
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Use version control, code review, testing and reproducible workflows to create maintainable analytical assets.
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Protect confidential information and follow cybersecurity, data governance, intellectual property and Responsible AI requirements.
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Continue developing domain knowledge in energy, engineering and industrial systems through hands-on work and mentorship.
Required Qualifications
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Recent graduate with a Bachelor's or Master's degree completed by the start date in Data Science, Statistics, Mathematics, Computer Science, Engineering, Operations Research, Physics or a related quantitative field.
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0-1 year of related experience in STEM
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Foundational knowledge of statistics, probability, experimental design and machine-learning concepts.
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Hands-on experience with Python or R through coursework, research, internships, co-ops or independent projects.
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Experience using common data analysis and visualization tools such as pandas, NumPy, scikit-learn, SQL, Jupyter, matplotlib, seaborn, Power BI or equivalents.
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Ability to explain technical work clearly in writing and conversation to both technical and non-technical audiences.
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Demonstrated problem-solving, collaboration, attention to detail and willingness to learn.
Desired Characteristics
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Internship, co-op, research, capstone or portfolio experience applying analytics or machine learning to a real problem.
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Exposure to cloud data platforms, distributed computing, data pipelines, Git, containers or ML lifecycle tools.
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Experience with time-series, simulation, optimization, computer vision, natural language processing or generative AI.
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Interest in renewable energy, physical systems, manufacturing or engineering applications.
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Experience validating results with subject-matter experts and incorporating feedback into an improved solution.
Eligibility Requirements:
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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.
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The required work location is Greenville, SC (relocation assistance is available)
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Unrestricted work authorization to work in the United States of America is required. We will not provide sponsorship for this role now or in the future.
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
GE Vernova offers a great work environment, professional development, challenging careers, and competitive compensation. GE Vernova is an Equal Opportunity Employer (https://www.eeoc.gov/sites/default/files/2022-10/22-088\_EEOC\_KnowYourRights\_10\_20.pdf) . 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 October 27, 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.
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.
How this job compares
Set against the 5,032 open Data Scientist jobs on Olive Jobs, counted October 28, 2026.
- Pay
- This posting$70–106K/yr
- South Carolina median$109–202K/yr31 salary ranges
- US median$135–217K/yr4,026 salary ranges
This range's midpoint, $88K, is 45% below the South Carolina median midpoint ($159K) — in the lowest quarter of Data Scientist salary ranges in South Carolina.
- Openings
- Olive Jobs lists 38 open Data Scientist jobs in South Carolina and 5,032 across the US. 5% of them nationwide are listed as remote or flexible.
- Hiring the most in South Carolina
- PwC10 open
- GE Vernova (this employer)4 open
- Indeed3 open
- Experience
- This posting asks for no prior experience — less than three in four Data Scientist postings that state a minimum ask for (median 5 years, across 4,335 postings).
- Education
- 2,827 of the 5,032 open Data Scientist jobs (56%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on October 28, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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