Bayer Posted September 3, 2026

Computer Vision and Data Analysis Co-Op (Chesterfield, Missouri, US)

Chesterfield, United States Type not listed
Data & Digital Intern/Fellow/Postdoc
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Bayer is the source of truth for this posting and owns the application process. We surface normalized context and market comparison you won't find on the original listing.

About this opportunity

Computer Vision and Data Analysis Co-Op

In this role, you will analyze and summarize data generated from field trials through digital phenotyping, applying modern computer vision and machine learning methods to support decision-making and identify opportunities for system and process improvements in collaboration with Field Testing, Data Science, and Computer Vision teams.

This position is based on a hybrid work model at the Bayer Crop Science facility in Chesterfield, Missouri. Regional travel includes nearby field testing sites in Illinois, with potential travel to other Midwest and Midsouth locations.

YOUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role include:

Analyze and interpret imagery and metrics generated from field trial data using advanced machine learning and computer vision techniques;

Collaborate closely with Field Testing and Data Science partners to integrate digital phenotyping insights into data analysis and model development;

Support experimental design by integrating insights from field assessments (UAV, remote sensing, and manual methods);

Contribute to system and workflow improvements by applying creativity and problem‑solving to large‑scale data challenges.

WHO YOU ARE

Bayer seeks an incumbent who possesses the following:

Required Qualifications:

Active M.S. or Ph.D. candidate in a relevant discipline (data science, precision agriculture, agricultural engineering, plant physiology, crop science, entomology, weed science, or pathology);

Proficiency in Python and experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX;

Solid understanding of core machine learning concepts (loss functions, regularization, optimization methods such as SGD/Adam, and learning rate scheduling);

Familiarity with agricultural research and field trial methodologies;

Basic knowledge of remote sensing technologies;

Ability to work collaboratively across areas of expertise.

Preferred Qualifications:

Hands‑on experience with modern architectures such as ResNet, UNet, DeepLab, YOLO, SegFormer, SAM, and Vision Transformers;

Experience with creating and managing large‑scale datasets, including the use of tools like Hugging Face Datasets;

One to two years of UAV imaging experience;

Strong analytical and problem‑solving skills;

Experience with cloud platforms (AWS, GCP, or Azure);

FAA Part 107 license to operate UAVs, or ability to obtain before the start date.

Employees can expect to be paid a salary of approximately between $22.75 to $47.75. Additional compensation may include a bonus or commission (if relevant).  Additional benefits may include health care, vision, dental, retirement, PTO, sick leave, etc (if relevant).  This salary (or salary range) is merely an estimate and may vary based on an applicant’s location, market data/ranges, an applicant’s skills and prior relevant experience, certain degrees and certifications, and other relevant factors.

This posting will be available for application until at least March 19, 2027

YOUR APPLICATION       Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and want to impact our mission Health for all, Hunger for none, we encourage you to apply now. Be part of something bigger. Be you. Be Bayer.

To all recruitment agencies: Bayer does not accept unsolicited third party resumes.

Bayer is an Equal Opportunity Employer/Disabled/Veterans

Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below.

Equal Opportunity Employer Statement: Notice for U.S. Visitors: All information on this site is subject to compliance with local rule and regulations as they may vary from time to time and across different geographies, including, without limitation, U.S. Executive Orders.       Bayer is an E-Verify Employer.               Location: United States : Missouri : Chesterfield      Division: Crop Science     Reference Code: 883370          Contact Us     Email: hrop_usa@bayer.com

Job details

Seniority
Intern/Fellow/Postdoc
Function
Data & Digital
Therapeutic area
Not listed
Location
Chesterfield, United States
Employment type
Not listed

How this role compares

Computed from every other active Data & Digital role in our database, not just this employer's listings.

We currently track 76 comparable Intern/Fellow/Postdoc Data & Digital roles across 20 biopharma companies.

76Comparable roles tracked
66Currently active
20Companies hiring similar roles
17Countries represented

Salary context

12 of 76 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.

This roleSubject Not listed on this posting
Highest disclosed · Advisor - AI/ML Generative Foundation Models for Biotherapeutics · Lilly $168,000/yr – $268,400/yr
Peer group range $75,510 – $218,200 (median $83,200)

Where these roles are based

Top locations among the 76 comparable roles

United States26
France12
Germany8
India6
Switzerland5
China5

+ 11 more countries

Seniority mix

76 of 76 peers have a known seniority level

Intern/Fellow/Postdoc56
Associate20

Therapeutic area mix

0 of 76 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden

No peers with a known therapeutic area yet.

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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.

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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.

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Unmatched or unknown dimensions score exactly the same: 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.