BullFrog AI
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.
Responsibilities
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.
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:
Minimum of 5‑8 years of post‑graduate experience in life sciences analytics, e.g., 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
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.
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Engineering, Information Technology, and Science
Industries Biotechnology Research and Technology, Information and Media
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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.
Responsibilities
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.
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:
Minimum of 5‑8 years of post‑graduate experience in life sciences analytics, e.g., 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
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.
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Engineering, Information Technology, and Science
Industries Biotechnology Research and Technology, Information and Media
#J-18808-Ljbffr