Data Science Co-Op (Berkeley, California, US)
About this opportunity
Data Science Co-Op
In this co‑op role, you will integrate and develop workflows for data analysis applications, evaluate machine learning and advanced statistical methods, and explore their applications in the biopharmaceutical industry to support process understanding, monitoring, and optimization in process development and GMP manufacturing environments.
Co-op Program Dates:
Spring Co-op: January 11, 2027 – June 11, 2027
Fall Co-op: May 17, 2027 or June 14, 2027 – December 10, 2027
YOUR TASKS AND RESPONSIBILITIES
The primary responsibilities of this role include:
Develop, test, and document software applications and methods to increase the efficiency of advanced data analytics applications in the biotechnology industry;
Use machine learning and advanced statistical methods to support process understanding, monitoring, and optimization;
Develop data analysis applications and workflows for mining, pre‑processing, and visualization of data;
Develop code in multiple programming languages (e.g., Python, R, etc.);
Support mining of process data from IT systems and databases;
Evaluate and apply different machine learning and advanced statistical methods;
Interact with data scientists to support activities and projects in the areas of bioprocess monitoring, root cause analysis, process understanding, and process improvements;
Communicate the outcome of development activities to the team;
Document project outcomes in a short technical report.
WHO YOU ARE
Bayer seeks an incumbent who possesses the following:
Required Skills and Experience:
Currently enrolled in a PhD program with a preferred focus in Engineering, Computer Science, Applied Math, or (Bio)Statistics;
Undergraduate degree in Engineering, Computer Science, Applied Math, or (Bio)Statistics;
Strong verbal and written communication skills;
Ability to deal professionally with internal customers of various organizational levels;
Ability to work effectively within the team and cross‑functionally;
Good organization, documentation, prioritization, and scheduling skills, together with an overall desire to learn;
Strong problem‑solving skills and critical thinking;
Ability to learn new technical topics;
Ability to work independently and multi‑task;
Interest in machine learning applications (some experience is preferred);
Programming experience in multiple languages/environments (such as Python, R, etc.);
Familiarity or experience with cloud environments (e.g., AWS, GCP, Azure) preferred.
Employees can expect to be paid an hourly rate of approximately between $22.75 to $45.50. 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 : California : Berkeley Division: Pharmaceuticals Reference Code: 882871 Contact Us Email: hrop_usa@bayer.com ]]>
Job details
How this role compares
Computed from every other active Biostatistics & Data Science role in our database, not just this employer's listings.
We currently track 26 comparable Intern/Fellow/Postdoc Biostatistics & Data Science roles across 8 biopharma companies.
Salary context
7 of 26 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 26 comparable roles
Seniority mix
26 of 26 peers have a known seniority level
Therapeutic area mix
1 of 26 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden
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.
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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.
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.