2025 Summer Intern - Data Science

Posted:
8/21/2024, 5:00:00 PM

Location(s):
Colorado, United States ⋅ Denver, Colorado, United States

Experience Level(s):
Internship

Field(s):
AI & Machine Learning ⋅ Data & Analytics

Workplace Type:
Remote

When can you expect to hear back?

We are committed to attending all career fairs and recruitment events before closing our positions. That means, this position might be open without updates for a few weeks to give us time to connect with all potential candidates before wrapping up the recruitment season. Check out our tentative timeline below to see when you can expect to hear from us! 

  • All postings close: September 28, 2024 

  • Interviews: Early to Mid October

  • Offers: By end of October

2025 Start Dates:

This position has opportunities to start in the Summer. Please see our start date below and let us know your availability.

  • Summer Internships: Monday, May 19, 2025 (40/hours per week max)

The Data Science Intern acts as part of a collaborative team to generate insights and product features from data. Contributes to the discovery, requirements gathering, data acquisition and wrangling, pipeline monitoring, and model prototyping and improvement processes.

What You'll Do

  • Participate in discovery, requirements gathering, and exploratory data analysis

  • Assist team data engineers and ML engineers with the development and optimization of our data and model pipelines, as well as data cleaning/wrangling

  • Work with team data scientists to prototype, test, and refine machine learning models to solve real-world problems, including in production environments

  • Gain experience with using machine learning at scale

What You'll Need

Minimum Qualifications

  • Currently pursuing an undergraduate or higher degree in statistics, mathematics, computer science, software engineering, or a related field is required

Preferred Qualifications

  • Hands-on programming experience

  • Using real-world data for projects, including data cleaning and preparation

  • Data science libraries like pandas, scikit-learn, caret, mlr, Tensorflow

  • Using the command line for development tasks

  • Basic knowledge of machine learning techniques such as classification, regression, and clustering

  • Familiarity with statistical concepts such as distributions, statistical testing, types of variables

  • Strong communication and organizational skills

  • Interest in expanding skills applicable within a data org

  • Source control systems such as Git

Travel Requirements and Working Conditions

  • Reliable internet access for any period of time working remotely, not in a Workiva office

  • Must be authorized to work in the United States and not require sponsorship now or in the future

How You’ll Be Rewarded

✅ Salary range in the US: $40.00 - $40.00

✅ 401(k) participation and match

✅ Paid sick leave

✅ A unique opportunity to further your learning experience through additional internship seasons

Workiva is an Equal Employment Opportunity and Affirmative Action Employer.  We believe that great minds think differently.  We value diversity of backgrounds, beliefs, and interests, and we recognize diversity as an important source of intellectual thought, varied perspective, and innovation.  Employment decisions are made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression genetic information, marital status, citizenship status or any other protected characteristic.  We strongly encourage and welcome people from historically marginalized groups to apply.

Workiva is committed to working with and providing reasonable accommodations to applicants with disabilities. To request assistance with the application process, please email [email protected].

Workiva employees are required to undergo comprehensive security and privacy training tailored to their roles, ensuring adherence to company policies and regulatory standards.

Workiva supports employees in working where they work best - either from an office or remotely from any location within their country of employment.