Data Scientist - I (Assistant)

Data Scientist – Contractor (Quantitative Biosciences)

Location: Rahway, NJ (Hybrid: 3 days onsite, 2 days remote)

Overview

Join a cutting-edge and innovative Quantitative Biosciences department focused on advancing drug discovery through computational science, high-throughput experimentation, and multidisciplinary collaboration.

We apply robust scientific methodologies, translational models, and advanced automation to better understand biological systems and molecular mechanisms, enabling the development of next-generation medicines.

This role offers the opportunity to work on complex, high-dimensional biological data across multiple modalities, directly supporting biologists and chemists in early-stage drug discovery.

Qualifications

• Minimum Education:
  Bachelor’s degree in Computational Physics, Chemistry, Bioinformatics, Computer Science, or another relevant quantitative field.
• Advanced Degrees (acceptable):
  Master’s or PhD in Computational Physics, Chemistry, Bioinformatics, Computer Science, or related disciplines.
• Experience:
  0–3 years of relevant experience.

Required Skills

• Proficiency in Python for scientific computing (e.g., NumPy, PyTorch, SciPy, pandas).
• Experience with high-performance computing (HPC) in Unix/Linux environments or cloud platforms (e.g., AWS).
• Hands-on experience in data science and machine learning.
• Working knowledge of biochemistry and/or chemistry.

Nice to Have

• Experience in pharmaceutical early drug discovery research.
• Exposure to advanced machine learning applications, especially in drug discovery contexts.
• Experience developing large-scale chemical foundation models, virtual screening models, or protein structure prediction models.

Responsibilities

As a Data Scientist within the Quantitative Biosciences team, you will:

• Develop machine learning and deep learning workflows to support novel drug discovery.
• Build and improve property prediction models for small molecules and peptides.
• Collaborate with interdisciplinary teams to apply computational and statistical methods for drug target identification and lead optimization.
• Analyze complex, high-throughput experimental datasets across multiple biological modalities.
• Conduct research in machine learning, molecular modeling, and computational biology.
• Communicate insights and analytical results clearly to scientific stakeholders, both verbally and in writing.
• Support experimental design by providing data-driven interpretation and guidance.

Role Summary

This role is ideal for candidates who are intellectually curious and interested in the intersection of machine learning, computational science, and drug discovery, with opportunities for growth in a highly collaborative research environment.