1

Python Biology Jobs in Santa Clara, CA (NOW HIRING)

We are seeking a driven, analytical Scientist, Computational Biology to join our early-stage ... High proficiency in Python and/or R , version control (Git), and working in cloud-based biobank ...

PhD in Bioinformatics, Computational Biology, Genomics, or a related field with 3+ years of ... Strong programming proficiency in Python and/or R is a plus * Experience building and running ...

next page

Showing results 1-20

Python Biology information

See Santa Clara, CA salary details

$15

$68

$101

How much do python biology jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for python biology in Santa Clara, CA is $68.85, according to ZipRecruiter salary data. Most workers in this role earn between $56.73 and $78.22 per hour, depending on experience, location, and employer.

What is the difference between Python Biology vs Bioinformatics Analyst?

AspectPython BiologyBioinformatics Analyst
Required CredentialsBiology degree, Python programming skillsBiology or related degree, Python and data analysis skills
Work EnvironmentResearch labs, biotech companies, academic institutionsResearch institutions, biotech firms, healthcare organizations
Industry UsageData analysis, modeling biological systems using PythonAnalyzing biological data, developing pipelines, interpreting results

Python Biology focuses on applying Python programming to biological research, often emphasizing coding and data modeling. Bioinformatics Analysts combine biological knowledge with data analysis skills, including Python, to interpret complex biological datasets. Both roles require programming skills and work in similar environments, but Python Biology is more research and development-oriented, while Bioinformatics Analysts focus on data interpretation and analysis.

Is Python useful for biology?

Python is widely used in biology-related jobs for data analysis, modeling, and automation of research workflows. Skills in Python, along with knowledge of biological data formats and libraries like Biopython, are valuable for roles in bioinformatics, computational biology, and systems biology.

How do Python biology professionals typically collaborate with interdisciplinary teams in research settings?

Python Biology professionals often work closely with biologists, data scientists, and software engineers to analyze complex biological data. Collaboration usually involves translating biological questions into computational tasks, developing data pipelines, and presenting findings in a way that is accessible to both technical and non-technical stakeholders. Regular meetings and code reviews are common practices, ensuring that the software developed aligns with the scientific goals of the project. This interdisciplinary approach not only enhances research outcomes but also provides valuable learning and growth opportunities for team members.

What are the key skills and qualifications needed to thrive as a computational biologist specializing in Python?

To thrive as a Computational Biologist with a focus on Python, you need a strong background in biology, bioinformatics, and programming, typically supported by a degree in biological sciences, computer science, or a related field. Familiarity with Python libraries like Biopython, NumPy, and pandas, as well as experience with data analysis tools and version control systems such as Git, is essential. Analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting biological data and collaborating with interdisciplinary teams. These competencies enable accurate data analysis, innovative research, and effective teamwork in advancing biological discoveries.

What is a Python biologist?

A Python biologist is a professional who uses the Python programming language to analyze and interpret biological data. They often work in fields like bioinformatics, genomics, and computational biology, developing software tools to process large datasets such as DNA sequences or protein structures. Python biologists help translate complex biological problems into computational solutions, enabling researchers to gain insights that would be difficult to achieve manually.
What job categories do people searching Python Biology jobs in Santa Clara, CA look for? The top searched job categories for Python Biology jobs in Santa Clara, CA are:
What cities near Santa Clara, CA are hiring for Python Biology jobs? Cities near Santa Clara, CA with the most Python Biology job openings:

Executive Director, Computational Systems Biology

Revolution Medicines

Redwood City, CA • Hybrid

Full-time

Re-posted 7 days ago


Job description

The Opportunity:

As an Executive Director and Head of Research Computational Biology within our Biology Function, the individual will oversee the scientific and strategic direction of systems biology research and preclinical computational biology initiatives. The individual will lead a team of computational biologists and bioinformaticians focused on acquisition, organization, and analysis of large multi-omics data sets, using both public and proprietary data sources, that will help inform treatment strategies and guide patient stratification for a growing pipeline of RAS(ON) and targeted oncology therapeutics. We are looking for an experienced leader with strong interpersonal skills and an ability to lead a strong and diverse computational biology team. Key aspects of the role include:

  • Strategic vision and leadership: Develop and implement a long-term strategy for research systems biology and bioinformatic activities to support a growing pipeline of RAS(ON) and novel targeted inhibitors. Lead and supervise a team of experienced computational biologists and bioinformaticians to generate, organize, and interpret large data sets to inform therapeutic and combination strategies for patients with cancer.

  • Cross-functional collaboration across research, translational, development and medical affairs groups: Work across functions to support advancement of programs from early discovery into clinical development using biological insights derived from computational approaches. Additionally, leverage clinical data from RVMD investigational agents to generate proprietary insights into RAS mutant tumor biology and RVMD RAS(ON) inhibitor mechanisms of action.

  • Technical leadership and innovation: Lead a team analyzing large, high-dimensional datasets. Work with colleagues in Information Sciences and Information Systems to oversee data integration, analysis and visualization using cloud-based platforms (AWS, Azure, GCP). Direct the development and application of cutting-edge statistical analysis, AI/ML methods, generative AI models, and MLOps principles to elucidate findings and generate new insights related to biomarker discovery, drug target identification, and predictive modeling. Establish and implement modern workflow management systems (Snakemake, Nextflow) and reproducible research practices.

  • External collaboration: Cultivate and manage academic and industry collaborations, including CRO partnerships. Represent the company at scientific conferences through presentations and thought leadership. Maintain an active publication record in high-impact, peer reviewed journals. Drive intellectual property strategy and patent filings related to computational discoveries.

Required Skills, Experience and Education:

  • Education: A Ph.D. in systems biology, computational biology, bioinformatics, or a related biological or biomedical discipline.

  • Experience: Minimum of 15+ years total experience with significant pharmaceutical/biotechnology industry and management experience.

  • Scientific knowledge: Deep expertise in systems biology, computational biology, and bioinformatics, including proficiency with multi-omics data integration, modeling, and analysis. Experience with single-cell technologies, spatial transcriptomics, proteomics, and epigenomics. Oncology research experience preferred but not required.

  • Technical: Advanced programming skills in R, Python, and at least one additional language (Perl, C/C++, Java). Proficiency with high-performance computing (HPC) and cloud platforms (AWS, Azure, or GCP). Knowledge of workflow management tools and version control systems. Understanding of MLOps principles, model deployment, and generative AI applications in drug discovery.

  • Leadership and management: Demonstrated ability to lead, mentor, and inspire interdisciplinary teams while fostering a collaborative culture. Experience managing budgets and strategic planning at the department level. Proven track record of advancing research programs from discovery through development.

  • Strategic thinking: Proven strategic thinker who can align research and drug development objectives and leverage innovative technologies effectively.

  • Communication: Excellent communication and presentation skills for interacting with technical teams, senior leadership, and external partners. #LI-Hybrid  #LI-GL1