Senior Data Scientist
Posted on 3/29/2023
Dorchester, Boston, MA, USA
Experience Level
Desired Skills
Data Science
Data Structures & Algorithms
  • A Masters in Computer Science, Data Science or related field, or equivalent industry experience
  • Experience with modern statistical analysis and machine learning techniques, particularly in the context of large-scale, high-throughput dataset analysis
  • An aptitude for learning about new domains and adapting machine learning techniques to those domains
  • Software engineering experience across multiple languages such as Python, Java, R
  • Strong analytical, problem-solving, and communication skills, including facility with Rmarkdown and/or Jupyter Notebooks for communicating reproducible results; and the ability to also condense, summarize, and synthesize those results into informative and actionable presentations to less technical audiences
  • Strong personal project management skills with practical experience managing your time split between multiple, parallel projects
  • B.S or M.S. in Chemistry, Computational Chemistry, or related field
  • Experience with cheminformatics tools and platforms such as JChem, RDKit, OpenBabel, Pipeline Pilot, KNIME, MOE, or Schrödinger
  • Experience with predictive drug development methods, such as pharmacophore models, crystal structure-based models, QSAR methods, or free energy calculations
  • Collaborate with data scientists, researchers, product teams, and other domain experts to design and implement solutions to complex data-oriented problems that impact real drug discovery programs
  • Work on a team developing novel algorithms for application in real-world preclinical discovery programs, tackling problems such as ADME modeling, toxicity prediction, and generative chemistry
  • Train, assess, deploy, and interpret statistical machine learning models that inform and advance our programs
Valo Health

51-200 employees

AI-powered drug discovery & development
Company Overview
Valo is a mission-driven technology company that was created with the belief that the drug discovery and development process can and should be better—faster, less expensive, and with a higher probability of success.