Data Science Co-op

The future is what you make it. When you join Honeywell, you become a member of our global team of thinkers, innovators, dreamers, and doers who make the things that make the future. That means changing the way we fly, fueling jets in an eco-friendly way, keeping buildings smart and safe and even making it possible to breathe on Mars. Working at Honeywell isn’t just about developing cool things. That’s why our employees enjoy access to dynamic career opportunities across different fields and industries. Are you ready to help us make the future? ABOUT THIS ROLE As a Data Science Co-op here at Honeywell, you will have the opportunity to apply your knowledge and skills in a real-world setting. You will work alongside our experienced data scientists and contribute to projects that drive data-driven decision-making and provide valuable insights to support business growth and operational excellence. Key Responsibilities Collaborate with cross-functional teams to identify business challenges and opportunities where data science can provide valuable insights Assist in developing and implementing advanced analytical models and methodologies to analyze complex data sets Support data visualization efforts to effectively communicate insights to stakeholders Conduct data analysis and provide actionable recommendations based on data-driven insights Stay updated with the latest trends and advancements in data science and identify opportunities to leverage new tools and technologies Through hands-on learning experiences, global exposure, networking, and professional development opportunities, Honeywell Co-ops will shape the future. You’ll have the opportunity to work alongside industry experts, lead initiatives that refine technical skills, and have unparalleled mentorship and growth opportunities that will elevate your career. Futureshaper Location: 1212 Pittsford-Victor Road, Pittsford, NY 14534 USA Pay Range: The hourly base range for this position is $23.00/hr - $38.00/hr. Please note that this salary information serves as a general guideline. Honeywell considers various factors when extending an offer, including but not limited to the scope and responsibilities of the position, the candidate's work experience, education and training, key skills, as well as market and business considerations. MINIMUM QUALIFICATIONS: Currently pursuing a degree in Data Science, Computer Science, Statistics, or a related field Strong analytical and problem-solving skills Currently pursuing a degree in Data Science, Computer Science, Statistics, or a related field Strong analytical and problem-solving skills Familiarity with data analysis and visualization tools Must graduate December 2025 or later Must continue enrollment in degree program upon completion of the Co-op Validated academic excellence (3.0 GPA and higher) Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. citizen, U.S. permanent resident, or have asylum or refugee status in the U.S WE VALUE: Enthusiasm for working in a collaborative team environment, including a willingness to seek and offer help. Familiarity with using LLMs, especially via APIs Understanding of application of dense vector text embedding models for finding semantic similarity NoSQL / Vector Database experience Knowledge Graph construction and search Cloud platform services experience on AWS or Azure Python programming Data visualization modules & packages, such as matplotlib, plotly, Power BI, etc Infrastructure as code BENEFITS OF INTERNING WITH HONEYWELL: Co-oping at Honeywell provides hands-on experience with cutting-edge technologies, professional development, and mentorship within a global organization. The application period for the Co-op position is estimated to be through the end of March 2025; however, this may be shortened or extended depending on business needs and the availability of qualified candidates. HoneywellURNAM Honeywell is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status.