About Us Valo 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.
About the Role As a Data Scientist II, Scientific Data Curation, you will collaborate with stakeholders across data science, data engineering, lab informatics, medicinal chemistry, and assay development to establish high quality, well-structured datasets for use within the Opal Computational Platform. These datasets will include biochemical, cellular, ADME, PK, cytotoxicity, and other assays related to drug discovery. We are looking for someone who is passionate about data, curious to explore the complexities of semi-structured datasets, and takes an intuitively quantitative approach to data exploration and curation. This role will include exploratory analysis of data, building scalable data pipelines to clean and harmonize data, and generation of visualizations, dashboards, and written communications to empower scientists across Valo to utilize large scale data as part of the Opal Platform.
What You Will Do - Develop standard procedures for establishing small molecule assay datasets used for modeling, including data cleaning, labeling, harmonizing, reporting, and QC
- Explore and evaluate new datasets to prioritize use at Valo
- Collaborate with relevant stakeholders to establish high quality, curated datasets for modeling
- Contribute to development and refinement of data standards and data models, and establish consistent internal terminologies and ontologies
What You Bring - Degree in a scientific field with 4+ (BS), 2+ (MS), or 0+ (PhD) years of experience
- Demonstrated ability to communicate with cross-functional stakeholders, including technical and non-technical audiences
- Experience with small molecule assay data (biochemical, cellular, ADME, PK, cytotoxicity)
- Demonstrated ability to clean, curate, and harmonize semi-structured data with SQL and python, with an eye towards generalizability and code re-usability
- A strong understanding of common ontologies, controlled vocabularies, knowledge bases, and databases related to drug discovery data (BioAssay ontology, NCBI taxonomy, HGNC, Uniprot, ChEBI, ChEMBL)
- Experience balancing tradeoffs between perfect and sufficient. Able to establish acceptable error rates, estimate expected errors in data, and communicate those expectations to broad audiences
Nice to Have - Understanding of FAIR data principles
- Experience with ontology management systems
- Experience with using generative AI for data cleaning and harmonization
- Experience with machine learning and building small molecule predictive models
More on Valo Valo Health, LLC ("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 diseases. Founded by Flagship Pioneering, Valo is headquartered in Lexington, MA with tissue engineering research based in New York, NY. To learn more, visit .