Data Scientist - Quantitative Biosciences

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Source Inc.

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Source Inc. isn’t just another staffing company, we’re a powerhouse of innovation, connecting top talent with the right opportunities. Recognized for 300% growth in the past three years, we operate in 34 countries with a global team of 5,500+. Our mission? To bridge the talent gap with precision—Right Talent. Right Time. Right Place. Right Price.

Data Scientist – Quantitative Biosciences

Rahway, NJ (Hybrid - 3 Days Onsite / 2 Days Remote)

06 months

Become part of a cutting‑edge and innovative Quantitative Biosciences department. Using robust scientific methodology, Client translational models, state‑of‑the‑art instruments, and automated equipment, we engage in multidisciplinary collaborations to Client the next medical breakthrough. We have expanded our capabilities to drive higher‑resolution interrogation of Client biology and the molecular mechanism of action of molecules that help advance the best drug candidates to the clinic.

Individuals joining us will have the opportunity to address challenging data problems, across multiple modalities with a hands‑on influence in delivering solutions directly to biologists and chemists designing the next generation of medicines. We operate in a truly multicultural, collegial, and collaborative work environment that is rich in development and growth.

• As a Data Scientist within the Quantitative Biosciences Department at client, you will lead statistical analyses and research data science solutions for small molecule and peptide workflows in early drug discovery.
• In the Quantitative Biosciences department, you will have the opportunity to explore the complex data output of cutting‑edge high‑throughput experimentation from across the organization.
• You will apply rigorous computational methods to help scientists generate Client and impactful hypotheses for target discovery.
• The Data Scientist will also provide stakeholders with an in-depth understanding of the data and interpretation of analytical results, providing expertise during the experimental development process.
• This is an ideal opportunity for candidates who are intellectually curious, want to work on the interface of computational science and drug discovery and look to grow in their next role.
• You should be able to communicate results effectively and concisely to stakeholders, both orally and in written format, balance priorities and build strong relationships among multidisciplinary cross‑organizational teams.

• Develop new machine learning workflows, including deep learning workflows, that enable the discovery of new medicines.
• Contribute to property prediction models for small molecules.
• Collaborate with interdisciplinary discovery teams to apply a variety of informatics and modeling techniques to identify new drug discovery leads and accelerate the evolution of leads to drug candidates.
• Conduct research in areas of machine learning and molecular modeling relevant to drug discovery.

• Minimum qualification:
  
  Bachelor in Computational Physics/Chemistry, Bioinformatics, Computer Science or another relevant quantitative field.
• Can submit candidates with Master's and PhD in Computational Physics/Chemistry, Bioinformatics, Computer Science or another relevant quantitative field.
• Years of experience: 0‑3 years.

• Skilled in Python for scientific computing (Num Py, PyTorch, etc.).
• Experience with high performance computing in a Unix/Linux OS environment, or familiarity with cloud computing, e.g., AWS experience.
• Hands‑on data science/machine learning experience.
• Working knowledge of biochemistry and/or chemistry.

• Experience with research projects in the pharmaceutical early discovery space.
• Experience with cutting‑edge machine learning applications and are motivated to jump in to see their application to drug discovery.
• Experience with developing large scale chemical foundation models for virtual screening applications and/or protein structure related models.

• Hybrid role (2 days remote and 3 days onsite).

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Source is an equal opportunity employer, dedicated to fostering a workplace where diverse talents and perspectives are valued. We make all employment decisions based on merit, ensuring a culture of respect, fairness, and opportunity for all, regardless of age, gender, ethnicity, disability, or other protected characteristics.