Data Science Eng Intern – Manufacturing Forecasting & Dashboards

Emerson

Boulder (CO)

On-site

USD 33,000 - 39,000

Full time

3 days ago
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Benefits offered by this job

Monthly housing allowance
Paid holidays
Professional development opportunities
On-site cafeteria

Job summary

Emerson in Colorado is seeking a data analytics intern to build predictive BI dashboards and forecasts that inform planning decisions. You will work with cross-functional teams to translate operational data into actionable insights and support SIOP discussions.

The role emphasizes hands-on training in data science as part of a manufacturing analytics project lifecycle. The ideal candidate is pursuing an engineering degree, eager to learn Python/R/SQL, and ready for full-time in-person work in a

Qualifications

  • 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

Responsibilities

  • Develop a Power BI dashboard predicting future past-due backlog using CRD, PSD, model code, and status.
  • Build weekly forecasts, heat maps, and simulations to quantify material and capacity impacts on backlog.
  • Create a predictive surge capacity model for low-volume lines to guide investments and lead times.
  • Apply data science methods (forecasting, modeling, visualization) to translate data into insights for planners.
  • Collaborate with planning, operations, and engineering to validate models and align with priorities.
  • Participate in data exploration through deployment and training across manufacturing analytics projects.

Skills

Analytical mindset
Curiosity
Data storytelling
Collaborative

Education

Bachelor’s degree in engineering

Tools

Power BI
Tableau
Python
R
SQL
Forecasting
Statistical modeling

Job description

Emerson in Colorado is seeking a data analytics intern to build predictive BI dashboards and forecasts that inform planning decisions. You will work with cross-functional teams to translate operational data into actionable insights and support SIOP discussions.

The role emphasizes hands-on training in data science as part of a manufacturing analytics project lifecycle. The ideal candidate is pursuing an engineering degree, eager to learn Python/R/SQL, and ready for full-time in-person work in a

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