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Drug Discovery Jobs (NOW HIRING)

Relay Therapeutics

VP, Head of Drug Discovery

Cambridge, MA · On-site

$230K - $328K/yr

The successful candidate will be a recognized leader in small molecule drug discovery with a proven track record of advancing programs from hit identification through IND filing. They will be a key ...

Deep Origin

VP/SVP of Drug Discovery

San Francisco, CA · On-site

About the Role We are seeking an experienced and highly strategic VP/SVP of Drug Discovery to lead and scale our discovery organization across target identification, hit discovery, lead optimization ...

Deep Origin

VP/SVP of Drug Discovery

Boston, MA · On-site

About the Role We are seeking an experienced and highly strategic VP/SVP of Drug Discovery to lead and scale our discovery organization across target identification, hit discovery, lead optimization ...

Deep Origin

VP/SVP of Drug Discovery

Boston, MA · On-site

About the Role We are seeking an experienced and highly strategic VP/SVP of Drug Discovery to lead and scale our discovery organization across target identification, hit discovery, lead optimization ...

Deep Origin

VP/SVP of Drug Discovery

Boston, MA

About the Role We are seeking an experienced and highly strategic VP/SVP of Drug Discovery to lead and scale our discovery organization across target identification, hit discovery, lead optimization ...

Deep Origin

VP/SVP of Drug Discovery

San Francisco, CA · On-site

About the Role We are seeking an experienced and highly strategic VP/SVP of Drug Discovery to lead and scale our discovery organization across target identification, hit discovery, lead optimization ...

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How much do drug discovery jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for drug discovery in the United States is $71.40, according to ZipRecruiter salary data. Most workers in this role earn between $58.17 and $83.41 per hour, depending on experience, location, and employer.

Is drug discovery a good career?

Drug discovery is a challenging and rewarding career that involves researching and developing new medications, often requiring strong skills in biology, chemistry, and data analysis. It offers opportunities for innovation, collaboration, and contributing to healthcare advancements, with roles available in pharmaceutical companies, biotech firms, and research institutions. Success in this field typically requires advanced degrees and staying current with scientific developments.

What are the key skills and qualifications needed to thrive in drug discovery, and why are they important?

To thrive in Drug Discovery, you need a strong background in biology, chemistry, pharmacology, and data analysis, typically supported by an advanced degree such as a PhD or PharmD. Familiarity with laboratory automation, bioinformatics platforms, high-throughput screening systems, and drug development regulatory requirements is often expected. Critical thinking, teamwork, and effective communication are crucial soft skills in this field. These competencies enable professionals to efficiently develop innovative therapies while navigating complex scientific and regulatory challenges.

How much does a drug discovery scientist make?

A drug discovery scientist's salary typically ranges from $70,000 to $130,000 annually, depending on experience, education, and location. Entry-level positions may start lower, while senior roles with advanced skills in molecular biology, pharmacology, or bioinformatics can earn higher salaries.

What is a drug discovery?

A Drug Discovery job involves researching and developing new pharmaceutical compounds to treat diseases. Professionals in this field work in multidisciplinary teams, including chemists, biologists, and pharmacologists, to identify and optimize potential drug candidates. The role includes tasks such as target identification, compound screening, preclinical testing, and collaboration with regulatory agencies. Drug discovery scientists often work in pharmaceutical companies, biotech firms, or academic research institutions to advance new therapies from concept to clinical trials.

How to get a job in drug discovery?

To get a job in drug discovery, candidates typically need a relevant degree such as a degree in chemistry, biology, pharmacology, or related fields, along with laboratory skills and experience in research. Gaining experience through internships, research projects, or working in pharmaceutical or biotech companies can improve prospects. Familiarity with drug development processes, data analysis tools, and strong analytical skills are also valuable for securing a position in this field.

What does a typical day look like for someone working in drug discovery?

A typical day in Drug Discovery involves designing and conducting experiments, analyzing biological or chemical data, and collaborating with cross-functional teams such as medicinal chemistry, computational biology, and clinical research. You may participate in project meetings, present findings, troubleshoot experimental issues, and ensure compliance with regulatory standards. The work environment is highly collaborative and often alternates between laboratory work, data interpretation, and strategic planning sessions. This dynamic routine allows professionals to contribute meaningfully at various stages of drug development, making the role both challenging and rewarding.

More about Drug Discovery jobs
What cities are hiring for Drug Discovery jobs? Cities with the most Drug Discovery job openings:
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Drug Discovery jobs near you
Infographic showing various Drug Discovery job openings in the United States as of August 2026, with employment types broken down into 93% Full Time, and 7% Part Time. Highlights an 93% In-person, and 7% Remote job distribution, with an average salary of $148,520 per year, or $71.4 per hour.

Director Machine Learning, Drug Discovery Analytics

Revolution Medicines

Redwood City, CA • Hybrid

Other

Posted 3 days ago

New

Job description

The Opportunity:

We are seeking a Director Machine Learning to lead the development of advanced machine learning approaches that accelerate small-molecule drug discovery. This role sits at the intersection of data science, chemistry, and biology, transforming complex scientific datasets into predictive models that guide target discovery, compound design, and translational hypotheses.

Working closely with experimental scientists, the Director ML will develop cutting-edge modeling approaches that integrate chemical, biological, and phenotypic data with their team. The successful candidate will play a key role in advancing a data-driven discovery strategy by designing predictive models, deploying innovative algorithms, and translating insights into actionable decisions that improve the speed and success of the discovery of medicines for patients with RAS-driven cancers.

Key responsibilities include:

Scientific Leadership:

  • Provide hands-on scientific leadership in drug discovery analytics spanning Identify opportunities where AI and advanced analytics can meaningfully improve scientific decision-making

  • Managing, coaching and mentoring scientists across the function in order to develop their skills and build RevMed's organizational capabilities

  • Define and lead machine learning strategies that accelerate early-stage drug discovery.

Model Development:

  • Develop predictive models for:

    • Compound activity, selectivity, ADME/Tox, and developability properties

    • Target engagement, mechanism-of-action, and phenotypic datasets

Cross-Functional Collaboration:

  • Work with biologists to interpret complex experimental datasets and generate mechanistic hypotheses.

  • Collaborate with data scientists and engineers and ML engineers to deploy models into scalable discovery workflows.

Required Skills, Experience and Education:

  • PhD in machine learning, computational chemistry, computational biology, computer science, or a related quantitative discipline.

  • 8+ years experience applying machine learning or advanced analytics to scientific problems.

  • Demonstrated experience working with chemical or biological datasets in drug discovery or related domains.

  • Strong expertise in:

    • Python-based ML ecosystems (PyTorch, TensorFlow, scikit-learn)

    • Data analysis and scientific computing (NumPy, Pandas)

    • Deep learning and representation learning techniques

  • Evidence of successful coaching, mentorship and development of both individuals and teams in order to build long-term organizational capability

  • Passion for scientific innovation and a relentless commitment to improving patient outcomes.

Preferred Skills:

  • Proven track record of applying advanced AI/ML approaches (deep learning, generative modeling, structure-based ML) to drug discovery or related life sciences domains.

  • Experience with cheminformatics or bioinformatics toolkits is highly desirable.

  • Familiarity with cloud computing and scalable ML workflows is a plus

  • Ability to work at the interface of computational and experimental science. 

    #LI-Hybrid  #LI-LN1

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