Intern - HP Quality Systems & Compliance (Columbus, United States, Ohio)
About this opportunity
Description
Boehringer Ingelheim is currently seeking a talented and innovative Intern to join our Human Pharma Quality Systems & Compliance department located at our Columbus, Ohio facility. As an Intern, you will work within Quality Systems supporting technical product complaints, data analytics, artificial intelligence initiatives, quality process improvement, supplier management, and strategic quality projects supporting commercial pharmaceutical products.
This role will focus on leveraging data-driven insights, Artificial Intelligence (AI), business intelligence tools, and industry best practices to enhance quality operations and support continuous improvement initiatives across Human Pharma Quality.
As an employee of Boehringer Ingelheim, you will actively contribute to the discovery, development and delivery of our products to our patients and customers. Our global presence provides opportunities for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the company’s success. We realize that our strength and competitive advantage lie with our people. We support our employees in a number of ways to foster a healthy working environment, meaningful work, diversity and inclusion, mobility, networking and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim's high regard for our employees.
Duties & Responsibilities
Support technical product complaint management activities, including trend analysis, process improvement initiatives, and quality metrics reporting.
Utilize data analytics tools, including Power BI, to develop dashboards, visualizations, and key performance indicators (KPIs) supporting Quality Systems operations.
Evaluate opportunities to leverage Artificial Intelligence (AI), Microsoft Copilot, automation, and digital solutions to improve quality processes and operational efficiency.
Support ongoing quality projects focused on complaint handling, supplier quality, documentation management, training effectiveness, and process optimization.
Research and benchmark pharmaceutical industry best practices related to Quality Systems, Technical Product Complaints, digital quality transformation, and AI-enabled quality operations.
Analyze internal quality data and industry trends to provide recommendations for process enhancements, automation opportunities, and future-state quality capabilities.
Assist with development of business cases, presentations, reports, and strategic recommendations for Quality leadership.
Collaborate with cross-functional stakeholders to identify opportunities to streamline and modernize quality processes while maintaining regulatory compliance.
Support continuous improvement initiatives through application of data science, analytics, and risk-based decision making.
Provide input and recommendations on strategic quality projects and future Quality Systems capabilities.
Requirements
Must be a current undergraduate, graduate or advanced degree student in good academic standing.
Student must be enrolled at an accredited college or university for the duration of the internship.
Overall cumulative minimum GPA from last completed quarter/semester 3.0 GPA (on a 4.0 scale) preferred.
Major or minor in related field of internship.
Undergraduate students must have completed at least 12 credit hours at current college or university.
Graduate and advanced degree students must have completed at least 9 credit hours at current college or university.
Desired Experience, Skills and Abilities:
Strong written, verbal, analytical, and presentation skills.
Demonstrated interest in Artificial Intelligence, Data Science, Business Intelligence, or Digital Transformation.
Experience with Power BI required; experience with Tableau or similar analytics platforms preferred.
Experience with Microsoft Copilot, Power Platform (Power Automate, Power Apps), or other AI-enabled technologies preferred.
Knowledge of data analysis, statistical methods, and visualization techniques preferred.
Experience with SQL, Python, R, or other data science tools preferred.
Ability to analyze large datasets and translate findings into actionable business recommendations.
Strong problem-solving and critical-thinking skills. Interest in pharmaceutical quality, operational excellence, and continuous improvement.
Proficient in Microsoft Suite, including Excel, Word, Teams, and PowerPoint.
Major in a scientific, technical, engineering, data science, analytics, or business discipline preferred.
Eligibility Requirements :
Must be legally authorized to work in the United States without restriction.
Must be willing to take a drug test and post-offer physical (if required).
Must be 18 years of age or older.
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Job details
How this role compares
Computed from every other active Quality role in our database, not just this employer's listings.
We currently track 34 comparable Intern/Fellow/Postdoc Quality roles across 16 biopharma companies.
Salary context
6 of 34 peers report a salary range (USD, annualized)
Peers share this role's job function and a matching or adjacent seniority level -- not necessarily the same therapeutic area or country.
Where these roles are based
Top locations among the 34 comparable roles
+ 7 more countries
Seniority mix
34 of 34 peers have a known seniority level
Therapeutic area mix
0 of 34 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden
No peers with a known therapeutic area yet.
Similar opportunities
The closest matches from our peer group, ranked by how similar they are, not how well you'd qualify for them -- treat this as market context, not a guaranteed shortlist; a weak match is labeled as one below.
Notify me about similar jobs
Get an email when we spot other openings like this one – same job function, comparable seniority, roles you'd actually want to see.
How we calculate "similar"
No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.
Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.
0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.