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Data Science Pharma Jobs in Colorado (NOW HIRING)

Inizio

Bilingual Clinical Educator

Denver, CO · On-site

$85K - $159K/yr

Previous experience in Pharma biotech as clinical educator or in sales preferred * Ability to ... with data, science, and technology to deliver bespoke engagement solutions that help clients ...

Agilent

Automation Controls Engineer

Frederick, CO

$103K - $161K/yr

Subject matter expert for GMP manufacturing process control systems, Supervisory Control and Data ... independent pharma/bioprocessing equipment. * Support on-the-floor automation/controls ...

Agilent

Automation Controls Engineer

Frederick, CO · On-site

$103K - $161K/yr

Subject matter expert for GMP manufacturing process control systems, Supervisory Control and Data ... independent pharma/bioprocessing equipment. * Support on-the-floor automation/controls ...

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Data Science Pharma information

What is data science in the pharmaceutical industry?

Data science in the pharmaceutical industry involves using advanced analytics, machine learning, and statistical methods to analyze complex data sets related to drug discovery, clinical trials, and patient outcomes. Data scientists in pharma help accelerate drug development, optimize clinical study designs, and identify new therapeutic targets by extracting meaningful insights from large volumes of biological and medical data. Their work improves decision-making, reduces costs, and ultimately leads to more effective treatments for patients.

What does a data science pharma do?

A data science professional in the pharmaceutical industry analyzes large datasets to identify patterns, support drug development, and improve patient outcomes. They use statistical methods, machine learning, and data visualization tools to inform decision-making and optimize research processes.

What is the difference between Data Science Pharma vs Data Analyst Pharma?

AspectData Science PharmaData Analyst Pharma
Required CredentialsBachelor's/Master's in Data Science, Statistics, or related fields; knowledge of programming languages like Python or RBachelor's in Statistics, Mathematics, or related fields; proficiency in Excel, SQL, and basic analytics tools
Work EnvironmentDeveloping predictive models, machine learning, advanced analytics in pharmaceutical R&D and marketingData reporting, visualization, and basic analysis to support decision-making in pharma companies
Employer & Industry UsagePharmaceutical companies, biotech firms, healthcare analytics providersPharmaceutical companies, healthcare organizations, research institutions

Data Science Pharma professionals focus on advanced analytics, machine learning, and predictive modeling to drive innovation in pharma. Data Analysts Pharma handle data reporting and basic analysis to support operational decisions. Both roles are essential but differ in complexity and technical requirements.

How does a data scientist in the pharmaceutical industry typically collaborate with cross-functional teams during drug development projects?

Data scientists in pharma regularly work alongside clinical researchers, biostatisticians, regulatory specialists, and product managers to analyze complex datasets from clinical trials and real-world evidence. They translate data-driven insights into actionable recommendations that guide decision-making throughout the drug development pipeline. Effective communication and teamwork are essential, as data scientists must both understand scientific objectives and explain analytical findings to colleagues from diverse backgrounds. This collaborative environment fosters innovation and ensures that data-driven approaches contribute meaningfully to advancing new therapies.

Do pharmacy companies hire data scientists?

Yes, pharmacy companies often hire data scientists to analyze clinical data, optimize drug development, and improve patient outcomes. These roles typically require skills in statistical analysis, machine learning, and programming tools like Python or R, and may involve working with large healthcare datasets in a regulated environment.

What are the key skills and qualifications needed to thrive as a data scientist in the pharmaceutical industry, and why are they important?

To thrive as a Data Scientist in pharma, you need a strong background in statistics, machine learning, and domain knowledge in biology or chemistry, usually backed by an advanced degree in a quantitative field. Familiarity with tools like Python, R, SQL, and experience with clinical trial data systems or bioinformatics platforms is commonly required. Strong analytical thinking, collaboration, and the ability to communicate complex data insights to multidisciplinary teams are vital soft skills. These capabilities are crucial for extracting meaningful insights from complex biomedical data, supporting evidence-based decision-making, and driving innovation in drug development.
What are popular job titles related to Data Science Pharma jobs in Colorado? For Data Science Pharma jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Data Science Pharma jobs in Colorado look for? The top searched job categories for Data Science Pharma jobs in Colorado are:
Data Science Pharma jobs near you
Infographic showing various Data Science Pharma job openings in Colorado as of August 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Remote job distribution.

Pri Sci/Sr Pri Sci/Assoc Director - In Vivo Pharmacology

Think Bioscience

Boulder, CO • On-site

$120K - $180K/yr

Full-time

Re-posted 22 days ago

Job description

In Vivo Pharmacology – Principal Scientist / Senior Principal Scientist / Associate Director
Think Bioscience:
We develop small-molecule drugs for historically challenging targets by using our synthetic biology platform to uncover novel mechanisms of biomolecular engagement (e.g., new functional pockets). Our team leverages expertise in synthetic biology, protein biophysics, applied enzymology, computational chemistry, and medicinal chemistry to advance small molecules with biochemical activities previously deemed difficult, if not impossible, to achieve. We are passionate about improving the lives of patients with innovative science. 
 
About the Position:
We are seeking an experienced pharmacologist to design and manage in vivo studies that advance our programs toward clinical candidates. This role will work closely with biologists, medicinal and computational chemists, and external CRO partners to build and execute our pharmacology and translational strategy. The ideal candidate has deep in vivo expertise, is excited to balance hands-on study management with high-level strategy discussions, and can move fluidly between disease areas (e.g., rare disease RASopathies and oncology). This is an on-site position in Boulder, CO.
Responsibilities:  
  • Serve as the in vivo pharmacology lead for several drug discovery projects. Establish in vivo strategy and study plans. Ensure that projects have all critical in vivo data to enable project stage dependent decisions.
  • Design, manage, and interpret in vivo pharmacology studies—including PK/PD, efficacy, and tolerability—to advance programs toward development candidates. 
  • Select, develop, and validate disease-relevant animal models.
  • Manage internal and external in vivo work, overseeing study quality, timelines, data integrity, and budget across multiple programs. 
  • Collaborate with chemistry and biology teams to integrate pharmacology, PK, and biomarker data to drive compound optimization across potency, selectivity, exposure, and safety. 
  • Oversee animal welfare and regulatory compliance, including IACUC protocol design and adherence to applicable in vivo study guidelines. 
  • Prepare and present study designs and data to internal teams and external partners, contribute to Think Bioscience's overall pharmacology and translational strategy, and contribute to nonclinical study reports supporting IND filings. 
 
Qualifications:
  • Ph.D. in pharmacology, physiology, biology, or a related discipline, with 5+ years of experience designing and managing in vivo studies in biotech or pharma (title and level commensurate with experience).
  • Demonstrated expertise designing, executing, and interpreting in vivo pharmacology studies (PK/PD, efficacy, tolerability, biomarker) and translating results into program decisions
  • Experience with disease-relevant animal models in rare and/or multisystem diseases—RASopathies or other genetically defined disorders strongly preferred
  • Familiarity with DMPK principles (clearance, oral bioavailability, exposure-response relationships) and ability to integrate PK/PD data into compound optimization decisions.
  • Expertise in oncology/immuno-oncology models or demonstrated adaptability across multiple therapeutic areas
  • Experience managing external CROs and collaborating across chemistry, biology, and DMPK teams; working knowledge of IACUC processes and animal welfare standards
  • Excellent oral and written communication skills, with the ability to present complex data to internal teams and external partners
  • Demonstrated productivity through patents, publications, and/or contributions to development candidates
 
What We Offer:  
  • Collaborative environment for innovative science and a mission-driven company 
  • Opportunity for technical expansion and professional growth 
  • Ability to influence key decisions in a fast-growing startup 
  • Equity participation in a well-capitalized company with differentiated platform technology and a first-in-class pipeline 
  • Competitive compensation and benefits package, including a salary range of $120,000-180,000 per year (title and salary commensurate with experience)  
 
Think Bioscience is an equal opportunity employer and committed to a diverse workplace. All applicants will be considered equally without regard to race, color, ethnicity, veteran status, religion, national origin, marital status, political affiliation, age, sex, sexual orientation, disability status, membership in an organization or any other non-merit factors.