SaaS - Flight Analytics Platform - Data Science Co-op - Spring 2027

CC2007 GE Flight Efficiency Services, Incorporated; Austin (TX); On-site; USD 48,000 - 60,000; Part time

Benefits offered by this job

Pay rate starting at $24/hour

Mentorship & professional development

Hands-on SaaS data projects

Job summary

GE Aerospace is seeking a curious Data Science Co-op to join our SaaS team in Austin, TX. You will partner across data science, software, product, and business units to solve problems with data and support product performance and customer outcomes.

This role provides practical experience, mentorship, and hands-on exposure to data-driven decision making in a fast-paced environment, with opportunities to build skills for future full‑time roles in data science, analytics, software, or related

Qualifications

• Enrolled in an accredited Associate/Bachelor’s/Master’s degree program (STEM or related).
• Minimum 3.0 GPA on a 4.0 scale, non‑rounded.
• Willing to work in Austin, TX.
• Reliable transportation to site.

Responsibilities

• Analyze product and business data to identify patterns, trends, risks, and opportunities.
• Build and improve dashboards, reports, and visualizations for informed decisions.
• Support development of data models and ML solutions for use cases like customer behavior, forecasting, segmentation, or optimization.
• Work with large datasets from product usage, customers, sales, and support.
• Collaborate with cross‑functional teams to translate business questions into analyses.
• Assist with data cleaning, feature engineering, validation, and exploratory analysis.
• Communicate findings clearly to technical and non‑technical stakeholders.
• Contribute to experimentation and measurement frameworks (A/B tests, KPIs).
• Document methods, assumptions, and results for reproducibility.

Skills

Python

R

SQL

Pandas

Jupyter

Education

Bachelor's degree in STEM or related field

Tools

Tableau

Power BI

Job description

Job Description Summary

We are looking for a curious, collaborative, and highly motivated Data Science Co-op to join our SaaS team.This is an opportunity for students who want to strengthen both their technical skills and business acumen while working on meaningful projects that influence real product and customer outcomes.As a Data Science Co-op, you will partner with teammates across data science, software engineering, product, and business functions to help solve problems using data.You will contribute to projects that improve product performance, customer experience, operational efficiency, and data-driven decision making.Along the way, you will learn from experienced professionals, build your network, and gain hands-on exposure to how data science supports growth in a SaaS environment.This co-op is designed to provide practical experience, professional development, mentorship, and the opportunity to build skills that can support future full-time roles in data science, analytics, software, or related technical functions.

Key Responsibilities

• Analyze product and business data to identify patterns, trends, risks, and opportunities.
• Build and improve dashboards, reports, and visualizations that help teams make informed decisions.
• Support development of data models and machine learning solutions for use cases such as customer behavior analysis, forecasting, segmentation, recommendation, or operational optimization.
• Work with large datasets from product usage, customer interactions, sales, support, and other business systems.
• Collaborate with cross-functional teams including engineering, product management, customer success, and operations to translate business questions into analytical approaches.
• Assist with data cleaning, feature engineering, validation, and exploratory analysis to improve data quality and model performance.
• Communicate findings clearly to both technical and non-technical stakeholders through presentations, summaries, and visual storytelling.
• Contribute to experimentation and measurement frameworks, including A/B testing, KPI tracking, and performance analysis.
• Document methods, assumptions, and results so work is reproducible, understandable, and actionable.
• Participate in team learning, mentoring, and professional development opportunities while gaining exposure to SaaS product and business operations.

Requirements

• Currently enrolled in an Associate’s, Bachelor’s, or Master’s degree program at an accredited university or in a credentialed technical training program; majors accepted are: Data Science, Statistics, Applied Mathematics, Computer Science, Computer Engineering, Informatics, Management Information Systems, Software Engineering, or another relevant STEM field.
• Experience with data analysis, statistics, programming, or software/data projects through coursework, internships, research, or personal projects.
• Minimum 3.0 cumulative GPA on a 4.0 scale, without rounding.
• Willing to work in Austin, TX.
• Reliable transportation, many of our sites do not have public transportation available.

Eligibility Requirements

Any offer of employment is conditioned upon the successful completion of a background investigation and drug screen. Legal authorization to work in the U.S. is required. We will not sponsor individuals for employment visas, now or in the future, for this job opening.

Desired Characteristics

• A strong candidate will have exposure to some of the following: Programming languages such as Python, R, or SQL; Data analysis and visualization tools such as pandas, Jupyter, Tableau, Power BI, or similar; Statistics and modeling techniques including regression, classification, clustering, or hypothesis testing; Data wrangling and exploratory analysis; Cloud, analytics, or SaaS data environments through coursework or projects.
• We are especially interested in candidates who are: Analytical and able to approach ambiguous problems with structured thinking; Personable and comfortable collaborating across technical and non-technical teams; Highly organized with strong attention to detail; Curious learners who are eager to grow technically and professionally; Self-motivated and able to manage tasks in a fast-paced environment; Effective communicators who can explain complex findings in simple terms; Adaptable and excited to work on evolving priorities and business needs; Customer-mind and interested in how data improves user and business outcomes.

Benefits

• Pay rates for this position begin at $24/hour and increase for each undergraduate year completed.
• Relocation support and housing assistance is available for those who relocate to a new city.
• GE Aerospace offers a great work environment, professional development, challenging careers, and competitive compensation.
• Relocation Assistance Provided: Yes

Equal Opportunity Statement

GE Aerospace 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 Aerospace 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). Employees may also be subject to random and reasonable‑suspicion drug and alcohol testing.

Company Culture

At GE Aerospace, we invent the future of flight, lift people up, and bring them home safely. We are a world-leading provider of jet engines, components, and integrated systems for commercial and military aircraft. At GE Aerospace, respect for people is core to our culture and commitment to FLIGHT DECK, our proprietary lean operating model. We attract, develop, and retain industry-leading talent from all backgrounds and cultivate communities where people are respected and empowered to reach their fullest potential. For the people of GE Aerospace, their work isn't just a job. It's their passion and purpose. We work and win as one team, accountable to each other and our customers, and we are always finding a better way to climb higher together. We were meant to fly.