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Full Time Science Communication Jobs (NOW HIRING)

... communication skills to make quantitative reasoning accessible to scientists with diverse ... At least 3 years of full-time relevant scientific experience post-PhD or equivalent * Strong ...

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Full Time Science Communication information

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How much do full time science communication jobs pay per year?

As of Jun 28, 2026, the average yearly pay for full time science communication in the United States is $109,595.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,500.00 and $142,000.00 per year, depending on experience, location, and employer.

What is the difference between Full Time Science Communication vs Science Writing?

AspectFull Time Science CommunicationScience Writing
CredentialsDegree in Science, Communications, or related fieldDegree in Science, Journalism, or related field
Work EnvironmentMedia outlets, science centers, public relationsPublications, online platforms, freelance
Employer & IndustryUniversities, research institutes, media companiesMagazines, websites, scientific journals

Full Time Science Communication involves creating engaging content to inform the public about science, often working in media or public outreach. Science Writing focuses on producing written content for publications or online platforms, emphasizing clarity and accuracy. While both roles require science knowledge and communication skills, Full Time Science Communication often includes multimedia and public engagement, whereas Science Writing centers on producing written articles and reports.

What are the key skills and qualifications needed to thrive as a Full Time Science Communicator, and why are they important?

To thrive as a Full Time Science Communicator, you need a solid background in scientific research or education, along with strong writing and verbal communication skills, often supported by a relevant degree in science or communications. Familiarity with media platforms, content management systems, and graphic or video editing tools is typically required. Creativity, adaptability, and the ability to translate complex concepts into accessible language are standout soft skills. These abilities are vital for effectively engaging diverse audiences, promoting scientific literacy, and fostering public trust in science.

What are some common challenges faced by professionals in full-time science communication roles, and how can they be addressed?

Full-time science communicators often face the challenge of translating complex scientific concepts into accessible language for diverse audiences without sacrificing accuracy. Balancing the needs of scientists for precision with the audience’s need for clarity can be demanding. Additionally, staying current with fast-evolving scientific developments and managing multiple projects or deadlines can require strong organizational and interpersonal skills. These challenges can be addressed through continuous learning, collaborating closely with subject-matter experts, and leveraging feedback from audiences to improve communication effectiveness.

What is full time science communication?

Full time science communication is a professional role dedicated to effectively sharing scientific information with non-expert audiences, such as the general public, policymakers, or students. Science communicators use various platforms—like writing, public speaking, digital media, or educational outreach—to make complex scientific ideas accessible and engaging. These professionals may work for universities, research institutions, museums, media outlets, or non-profit organizations. Their work is vital for increasing public understanding of science, fostering informed decision-making, and inspiring interest in scientific topics.
What cities are hiring for Full Time Science Communication jobs? Cities with the most Full Time Science Communication job openings:
What are the most commonly searched types of Science Communication jobs? The most popular types of Science Communication jobs are:
Quantitative Biologist

Quantitative Biologist

Arcadia Science

Emeryville, CA • On-site, Remote

Full-time

Posted 26 days ago


Key responsibilities

  • Design and implement software for signal processing, image analysis, and quantitative interpretation of experimental data.

  • Develop and maintain scalable workflows and pipelines for high-dimensional phenotypic data across diverse data types.

  • Collaborate with experimental biologists to design statistically sound experiments before data is collected.


Job description

A Bit About Us

We are Arcadia Science, an evolutionary biology company founded and led by scientists. Our mission is to turn natural innovations into real-world solutions by developing systematic and quantitative approaches to leveraging biology for therapeutics R&D. We share our research as openly as possible to accelerate discovery and make our work broadly useful.

The Opportunity

We're closing the gap between biological data and biological understanding. Our Validation team does this by closing the design–build–test–learn loop through lab validation across diverse organisms. Read more about our work through our publications.

We are seeking a Quantitative Biologist to join our Validation team with strong expertise in using computational analyses across modalities and biological scales to extract meaning from complex data, identifying the limits of existing analytical approaches, and developing new ones to address them. In this role, you will work shoulder-to-shoulder with experimental biologists, and bring your own firsthand experience at the bench to inform how data is collected, analyzed, and interpreted. You’ll work with imaging modalities (Raman spectroscopy, coherent Raman imaging, live-cell microscopy, quantitative phase imaging) and a range of other quantitative measurements across diverse organisms. Your contributions will be instrumental in validating existing tools at Arcadia, shaping how we design and interpret experiments, identifying potential assets, and building robust analytical infrastructure that scales across the team.

Top candidates are rigorous, collaborative scientists who are equally at home writing computational pipelines and sitting down with a wet-lab colleague to think through a statistical analysis. They have strong intuitions about image data, high expectations for rigorous experimental design, and the communication skills to make quantitative reasoning accessible to scientists with diverse backgrounds. They have hands-on bench experience, generating biological data themselves and understanding the experimental realities that shape what analysis is even possible. Enthusiasm and independent documentation for participation in open science is also required as we routinely share our findings via our open-source pubs.

Key Responsibilities
  • Design and implement software for signal processing, image analysis, and quantitative interpretation of experimental data

  • Develop and maintain scalable workflows and pipelines that apply these methods to high-dimensional phenotypic data across diverse data types

  • Collaborate with experimental biologists to design statistically sound experiments before data is collected

  • Build and apply statistical and machine learning models to interpret complex biological datasets, including mixed-effects models, dimensionality reduction, and other approaches

  • Review and improve code written by scientists across the team, promoting reproducible and well-documented analytical practices

  • Develop SOPs and shared infrastructure (pipelines, notebooks, documentation) that help the broader team work more quantitatively and independently over time

  • Synthesize ideas, data, and findings into fully open-access pubs and engage with the scientific community to maximize impact and garner feedback that improves the work

Qualifications
  • Ph.D. or equivalent experience in biology, bioengineering, computational biology, biophysics, cell biology, or a related field

  • At least 3 years of full-time relevant scientific experience post-PhD or equivalent

  • Strong foundation in statistically driven experimental design with hands-on experience applying these to biological datasets

  • Track record of working directly with experimental scientists to design, analyze, and interpret studies

  • Demonstrated expertise developing software for biological image analysis

  • Experience with statistical or machine learning methods applied to phenotypic biological data, including spectral or image data

  • Proficiency in Python and/or R for data analysis, pipeline development, and code review

  • Experience with instrument control, data acquisition software, or pipelines connecting hardware to analysis

  • Direct bench experience generating biological data, with a working understanding of common sources of experimental variability and how they manifest in downstream analysis

  • Excellent verbal and written science communication skills for both general and technical audiences, as we expect all scientists to actively draft and openly publish their results

Successful applicants can expect to be compensated between $150,000–$200,000 with benefits and a competitive equity offering, depending on experience level. The position will require the individual to be on-site at our Emeryville, California headquarters.

Arcadia is an equal opportunity workplace; we welcome people from all backgrounds and communities. We provide competitive compensation and practical benefits to keep you happy and healthy so that you can do your best work.

Please note that an offer of employment at Arcadia is contingent upon the successful clearance of a reference and background check.