About UsValo Health is a technology company that is integrating human-centric data and AI-powered technology to accelerate the creation of life-changing drugs for more patients faster. Valo was created with the belief that the drug discovery and development process can and should be faster and less expensive, with a much higher probability of success. We are using models early to fail less often, executing clinical trials to add valuation to the company, and generating fit-for-purpose data to feed back into Valo’s Opal Computational Platform as we reinvent drug discovery and development from the ground up. Disease doesn’t wait, so neither can we.
We are a multi-disciplinary team of experts in science, technology, and pharmaceuticals united in our mission to achieve better drugs for patients faster. Valo is committed to hiring diverse talent, prioritizing growth and development, fostering an inclusive environment, and creating opportunities to bring together a group of different experiences, backgrounds, and voices to work together. We achieve the widest-ranging impact when we leverage our broad backgrounds and perspectives to accelerate a new frontier in health. Valo seeks to become the catalyst for the pharmaceutical industry and drive the digital transformation of the industry. Are you ready to join us?
About The RoleAs a
Senior Staff Scientist ML within the Translational Biology Data Science department, you will be a core member of a team of data scientists, software engineers, and translational biologists building a powerful computational platform for advancing the research and development of new medicines. You will develop graph ML solutions to make available a vast corpus of knowledge in medicine, molecular biology, human genetics, and drugs available to machine learning-based strategies and compute-enabled hypothesis generation. Successful candidates will work with a diverse set of scientists, entrepreneurs, and domain experts in ways that cut across traditional industry boundaries.
What You’ll Do…- Work as part of teams of world-class data scientists and engineers developing and deploying robust, generalizable solutions to core scientific problems.
- Use your technical knowledge and intuition to articulate and break down large problems into solvable pieces. Time is limited, you’ll need to prioritize which problems are critical-path today from those that can wait.
- Collaborate with drug discovery and clinical teams to help ensure the relevance and impact of the models, algorithms, or knowledge representation developed by you and your team. Be comfortable with scientific risk - many of the challenges we’re trying to address don’t have known solutions.
- Be a dynamic and active team member, providing regular updates of your work and input into the work of your colleagues; championing data science best practices; participating in code, design, and analysis review.
What You Bring...- MS or PhD in a quantitative field with a demonstrated experience at the intersection of deep learning and knowledge graphs.
- Advanced knowledge of and extensive experience with graph ML techniques such as Graph Neural Network (GNN) models applied to link prediction, node classification, and other biomedical-relevant computational tasks, as well as related explainability methods.
- Experience or general knowledge of knowledge-graph building and graph databases.
- Familiarity with general graph algorithms and relevant Python libraries.
- Strong experience in Python and at least one deep-learning framework (e.g., pytorch).
- Experience with data science best practices (data provenance, code versioning, reproducibility, etc.), large-scale data analytics engines (e.g., Spark or Dask), and working in cloud environments (e.g., AWS).
- Domain knowledge: Experience in healthcare, medicine, molecular biology, computational biology, or life sciences preferred.
- Familiarity with or exposure to traditional drug discovery and development processes and approaches is a plus.
More on ValoValo Health, Inc (“Valo”) is a technology company built to transform the drug discovery and development process using human-centric data and artificial intelligence-driven computation. As a digitally native company, Valo aims to fully integrate human-centric data across the entire drug development life cycle into a single unified architecture, thereby accelerating the discovery and development of life-changing drugs while simultaneously reducing costs, time, and failure rates. The company’s Opal Computational Platform is an integrated set of capabilities designed to transform data into valuable insights that may accelerate discoveries and enable Valo to advance a robust pipeline of programs across cardiovascular metabolic renal, oncology, and neurodegenerative disease. Founded by Flagship Pioneering and headquartered in Boston, MA, Valo also has offices in Lexington, MA, and New York. To learn more, visit www.valohealth.com.
