Principal Data Scientist (Biomedical)

Do you want to be at the forefront of AI drug discovery and advance the next generation of lifesaving medicine? Now's your opportunity!

BullFrog AI, a technology-enabled drug discovery company, uses AI to aid in advancing the next generation of lifesaving medicine. We are at the intersection of computational biology and Artificial Intelligence, and we're seeking an exceptional Senior Data Scientist with a strong background in biomedical analytics to join our growing team. The selected candidate will have the opportunity to work on cutting-edge projects that integrate AI-driven analytics with groundbreaking biomedical research

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Position Overview:

We are seeking an exceptional Principal Data Scientist with a strong background in biomedical analytics to join our growing team. The selected candidate will have the opportunity to work on cutting-edge projects that integrate AI-driven analytics with groundbreaking biomedical research.

In this role, the senior data scientist will support individual projects from an execution and leadership perspective. The day-to-day work will be client-dependent with flavors of target discovery, patient subtyping, and exploring multimodal and/or mixed data to gain insights. Additionally, they will build and provide technical contributions to the company’s in-house platform.

Location: Remote within the United States.

The senior data scientist will also:

• Design, implement, and optimize AI models using diverse healthcare data.
• Engage in multi-modal genomic analyses such as RNA-Seq differential expression, clustering, and GWAS.
• Implement NLP solutions tailored to life sciences data sets.
• Collaborate effectively with remote teams to ensure seamless communication and delivery.
• Educate and present complex data science findings to non-technical stakeholders, ensuring clarity and actionable insights.

Requirements

Education:

• Bachelor's degree from a top-ranking university in the United States or the United Kingdom.
• An advanced degree (MS or PhD) in a quantitative field such as biology, computer science, or engineering, from a top-ranking university in the United States or the United Kingdom.

Professional Experience:

• A minimum of 5-8 years of post-graduate experience in life sciences analytics, e.g., in Pharma, Biotech, or Consulting.
• Experience with major healthcare data types, including -omics (required), claims data, and clinical data (e.g., EHR).
• At least 1 year of experience working with large language models.
• A maximum of 8-10 years of post-PhD experience.
• Demonstrated coding proficiency in Python.Proven track record of collaborating with remote teams.
• Proficient and fluent in the English language.

Other: Must be legally authorized to work in the United States and be a United States citizen.

Desired Skills:

• Prior experience in multi-modal analysis with deep learning.
• Causal inference experience is a significant plus.
• NLP/LLM expertise applied to life sciences and healthcare text.
• Strong foundation in data engineering and databases.
• Experience with graphs, including feature engineering, machine learning, and visualizations.
• Cloud platform experience, particularly AWS or Google Cloud.
• Demonstrated ability to deliver complex data science outputs to senior leadership.

Benefits:

• Benefits:15 days of paid time off annually
• 11 paid holidays annually
• Medical, Dental, and vision coverage with eligibility on the first day of employment
• Short-Term Disability
• 401 (k) with enrollment upon day one
• Eligibility for bonus and stock options based on a combination of individual and company performance.