Lead Data Scientist - Drug Discovery

About the Role

Our client seeks a highly experienced Lead Data Scientist to spearhead their efforts in Drug Discovery . This is a remote position, allowing you to contribute from anywhere. You will lead a team of data scientists and collaborate with chemists, biologists, and pharmacologists to accelerate the identification and development of novel therapeutics. Your expertise in machine learning, statistical modeling, and handling complex biological data will be instrumental in uncovering new drug candidates and optimizing existing pipelines.

This role offers a unique opportunity to shape the future of pharmaceutical research within a forward-thinking, remote-first organization that champions scientific excellence and innovation.

• Lead and mentor a team of data scientists focused on drug discovery projects.
• Develop and deploy advanced machine learning models for target identification, lead optimization, and predictive toxicology.
• Manage and analyze diverse datasets including chemical, biological, and clinical trial data.
• Collaborate closely with cross-functional R&D teams to integrate data-driven insights into the drug development process.
• Present research findings and strategic recommendations to senior management and external stakeholders.

• Ph.D. or Master's degree in a quantitative field such as Data Science, Computer Science, Statistics, or Cheminformatics.
• 10+ years of experience in data science, with a significant portion focused on the pharmaceutical or biotechnology industry.
• Expertise in machine learning techniques (deep learning, reinforcement learning, etc.) and their application to biological problems.
• Proficiency in programming languages like Python or R and experience with relevant libraries (e.g., Tensor Flow, PyTorch, Scikit-learn).
• Demonstrated experience in leading research projects and managing scientific teams.

• Highly competitive salary and significant bonus potential.
• Comprehensive medical, dental, and vision benefits package.
• Generous stock options or equity grants.
• Extensive opportunities for professional development and attending international conferences.
• A stimulating remote work environment with a strong emphasis on collaboration and scientific impact.