Back to jobs

Data Science Engineering Intern

Boulder, CO, United States

Pay
$24–28/hourVaries by grade — pay source
We recognize the importance of employee wellbeing. Our culture prioritizes work-life balance and offers flexible time off plans, including monthly housing allowance, paid holidays, employee choice hours, paid sick time, and paid volunteer time. You will also get hands-on experience, professional development, and networking opportunities in our well-established and structured internship program. There are also easy to access on-site cafeterias, fitness facilities, employee resource groups, recognition, and much more. At Emerson, our employees’ passion for innovation and results drives our success. We actively pursue new technologies, capabilities and approaches to drive tangible value for our customers. To reward this passion for innovation and results, Emerson makes meaningful investments in our people. We provide competitive compensation, integrated benefits offerings, and fulfilling career journeys that support the growth of each employee. We firmly believe that when Emerson is successful in achieving its operational and financial goals, our employees share in the company’s success. The hourly pay for this role is $24-$28, commensurate with the year in school and experience each candidate brings to a role. This position will be open for a minimum of 7 days from the day of posting. Applicants are encouraged to apply early to receive optimal consideration. In compliance with the Colorado Job Application Fairness Act, in any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information
Read the full posting
Work setup
Unconfirmed
Employment
Unconfirmed
Apply at Emerson

What you’ll bring

All qualifications

Core experience

  • Ability to work full-time (40 hours) per week in-person
  • Experience with Power BI, Tableau, or similar data visualization platforms
  • Familiarity with Python, R, SQL, or statistical modeling techniques
Qualification wording
Ability to work full-time (40 hours) per week in-person
Experience with Power BI, Tableau, or similar data visualization platforms
Familiarity with Python, R, SQL, or statistical modeling techniques
Education & alternatives
For This Role, You Will Need: - Pursuing a bachelor’s degree in engineering - Zero (0) years of related experience

Tools in this posting

  • Python
  • R
  • SQL
  • Tableau
  • Power BI
Source — Tool mentions in context
- Experience with Power BI, Tableau, or similar data visualization platforms - Familiarity with Python, R, SQL, or statistical modeling techniques - Prior internship or project experience in data analytics, operations research, or supply chain
Preferred Qualifications That Set You Apart: - Experience with Power BI, Tableau, or similar data visualization platforms - Familiarity with Python, R, SQL, or statistical modeling techniques
In This Role, Your Responsibilities Will Be: - Develop a Power BI dashboard that predicts future past-due backlog based on Customer Required Date (CRD), Planned Ship Date (PSD), model code, value stream, and material status, enabling planners to answer, "What will be late next month?" with data-driven confidence. - Build weekly projected late backlog forecasts, top model code risk heat maps, and simulation tools that quantify the impact of material availability, capacity constraints, and scheduling decisions on backlog recovery.

Job description

View original posting ↗

In This Role, Your Responsibilities Will Be:
  • Develop a Power BI dashboard that predicts future past-due backlog based on Customer Required Date (CRD), Planned Ship Date (PSD), model code, value stream, and material status, enabling planners to answer, "What will be late next month?" with data-driven confidence.
  • Build weekly projected late backlog forecasts, top model code risk heat maps, and simulation tools that quantify the impact of material availability, capacity constraints, and scheduling decisions on backlog recovery.
  • Create a predictive surge capacity model for low-volume product lines (e.g., CMFHC) that identifies demand mix variation, highlights bottlenecks by operation, and produces growth scenario analyses to guide investment prioritization and lead time stability.
  • Apply data science methodologies, including statistical modeling, forecasting, and visualization, to translate complex operational datasets into actionable insights for planners, operations leaders, and SIOP discussions.
  • Collaborate with cross-functional teams including supply chain planning, operations, and engineering to validate models, gather requirements, and ensure analytical tools align with business priorities and decision-making workflows.
  • Participate in multiple analytical projects at various stages, from data exploration and model development to dashboard deployment and user training, gaining a comprehensive understanding of the data science project lifecycle in a manufacturing context.

 
Who You Are:
  • You are analytically minded and naturally curious, energized by turning raw data into clear, actionable insights. You take initiative in exploring new tools and methodologies, and you're not afraid to dive into ambiguous problems to find structure and meaning. You communicate complex findings in ways that resonate with both technical and non-technical audiences. You thrive in collaborative environments and build strong relationships across teams, bringing enthusiasm and rigor to every project you touch.

 
For This Role, You Will Need:
  • Pursuing a bachelor’s degree in engineering
  • Zero (0) years of related experience
  • Ability to work full-time (40 hours) per week in-person
  • Legal authorization to work in the United States

 
Preferred Qualifications That Set You Apart:
  • Experience with Power BI, Tableau, or similar data visualization platforms
  • Familiarity with Python, R, SQL, or statistical modeling techniques
  • Prior internship or project experience in data analytics, operations research, or supply chain
  • Exposure to manufacturing, supply chain planning, or ERP/MES systems

 
Our Culture & Commitment to You:
  • At Emerson, we prioritize a workplace where every employee is valued, respected, and empowered to grow. We foster an environment that encourages innovation, collaboration, and diverse perspectives – because we know that great ideas come from great teams. Our commitment to ongoing career development and growing an inclusive culture ensures you have the support to thrive. Whether through mentorship, training, or leadership opportunities, we invest in your success so you can make a lasting impact. We believe diverse teams working together are key to driving growth and delivering business results.
  • We recognize the importance of employee wellbeing. Our culture prioritizes work-life balance and offers flexible time off plans, including monthly housing allowance, paid holidays, employee choice hours, paid sick time, and paid volunteer time. You will also get hands-on experience, professional development, and networking opportunities in our well-established and structured internship program. There are also easy to access on-site cafeterias, fitness facilities, employee resource groups, recognition, and much more. 
  • At Emerson, our employees’ passion for innovation and results drives our success. We actively pursue new technologies, capabilities and approaches to drive tangible value for our customers. To reward this passion for innovation and results, Emerson makes meaningful investments in our people. We provide competitive compensation, integrated benefits offerings, and fulfilling career journeys that support the growth of each employee. We firmly believe that when Emerson is successful in achieving its operational and financial goals, our employees share in the company’s success. The hourly pay for this role is $24-$28, commensurate with the year in school and experience each candidate brings to a role.
  • This position will be open for a minimum of 7 days from the day of posting. Applicants are encouraged to apply early to receive optimal consideration. In compliance with the Colorado Job Application Fairness Act, in any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information

     

#LI-KT1

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.

Complete your application on hdjq.fa.us2.oraclecloud.com. The employer’s form will show what is required.

Already applied? Track this application

Source & posting history

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

This passage needs a closer read in the full description.

Location & working pattern

Boulder, CO, United States

This passage needs a closer read in the full description.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Status in our records
Active
First seen by us
Sep 1, 2026
Recorded sightings
63
Last seen by us
Oct 9, 2026

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

Report an error

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.