Senior Computational Biologist
The Company
We are Alloy Therapeutics—a biotechnology ecosystem company empowering the global scientific community to make better medicines together. Through a community of partners, we democratize access to pre-competitive tools, technologies, services, and company creation capabilities that are foundational for discovering and developing therapeutic biologics. The company facilitates affordable, non-exclusive access to the entire drug discovery community from academic scientists, small and medium biotech, to the largest biopharma. At Alloy, we believe our industry should compete on getting the best drugs to patients as quickly as possible, not exclusive access to the best platforms. As a reflection of our relentless commitment to the scientific community, we reinvest 100% of its revenue in innovation and access to innovation. MAY THE BEST DRUG WIN.
Alloy is headquartered in Waltham, MA with additional labs in Basel, CH; Cambridge, UK; and Athens, GA. Successful members thrive in our shared culture of accountability, deliberate trust, and open communication. As a team we aspire to work together to exceed expectations and collectively contribute across the global organization to always maintain our nimble, startup culture. Come thrive at Alloy!
The Team
The Senior Computational Biologist will join the Insights team. This team builds internal and external software products that power Alloy’s operations, partner portals, and data platforms. Team members collaborate closely with engineering, product, and scientific teams to deliver modern, scalable, and intuitive web applications and data science solutions supporting Alloy’s mission of accelerating drug discovery through technology.
The Role
As a Senior Computational Biologist, you will work with an interdisciplinary team of biologists, computer scientists, and computational chemists to support Alloy’s drug discovery & engineering efforts across various modalities, focusing on antibody and TCR-based drugs. The successful candidate will have a deep understanding of common machine learning concepts & theory and has demonstrated their ability to translate theoretical knowledge to real-world applications in drug discovery & engineering. The individual has experience working with protein structures (preferably of antibodies and TCRs), next-generation sequencing (NGS) datasets of immune repertoires or in-vitro selections and complementary omics or functional datasets used to inform discovery and engineering decisions. Additional expertise in other drug modalities is considered a plus.
This role requires a deep scientific interest in modern, data-centric approaches to drug discovery (demonstrated by your scientific publication record) and a passion for improving wet-lab workflows with meaningful computational methods. The individual is expected to be highly organized, accountable for their deliverables, and be able to work independently with minimal day-to-day supervision. The successful candidate will be able to grow in this role by taking on more responsibilities as well as representing the team at scientific meetings & conferences.
You will report to the Head of the Research and Technology of the Insights division, Cédric Weber, and have autonomy in owning multiple projects, collaborating with international teams, and delivering scientific insights.
How You’ll Drive Impact
- Learn: You are genuinely interested in your research area and love to stay at the forefront of science.
- Innovate: You will develop novel computational approaches for drug discovery & engineering and work with colleagues to implement these in real-world applications.
- Collaborate: You enjoy exchanging ideas with others and love to work in a team environment where the whole team as a group drives impact.
- Lead: You are a self-starter, able to lead and manage yourself. You inspire others by going the extra mile and paying attention to details that others miss.
- Communicate: You can communicate new ideas & insights clearly and engagingly, not only to experts in your field but also to non-experts and senior management.
Why We Value You
- You have a strong background in Mathematics, Statistics, Computational Biology, or related fields, Ph.D. is preferred.
- You have a proven track record of applying data analysis techniques to drive decision-making in drug discovery, drug development, or drug manufacturing workflows
- You have hands-on experience applying machine learning models to biological datasets such as next-generation sequencing data, protein characterization data and protein structures.
- You have prior experience supporting the direct discovery and characterization of large-molecule drugs.
- You have a good understanding of common machine-learning concepts and statistical theory.
- You possess a deep understanding of modern machine and deep learning approaches, with a focus on transformer-based architectures, graph neural networks, and geometric deep learning.
- You are proficient in Python and are familiar with common libraries and frameworks such as scikit-learn, XGBoost, Tensorflow, and PyTorch.
- You have basic experience working in cloud environments, preferably AWS.
- You understand how to deploy machine learning systems to production using tools such as MLflow, ONNX, and others.
- You are familiar with good software development practices and tools like unit testing, CI/CD, Git and Code reviews.
- You are fluent in English and highly communicative, transparent, and collaborative with research and informatics peers.
Desired Multipliers
- Familiarity with RDBMS concepts, SQL and NoSQL databases
- Additional knowledge of cloud computing infrastructure (networking, security, storage) and their operation and configuration (AWS preferred)
- Ability to work across various international time zones
- Accommodate occasional travel as needed (10%)