Data Scientist

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.

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.

• 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.

• 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, Num Py, 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.

• 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.

Yes

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,…