Staff Data Scientist, Valo Health

• This hybrid role is ideal for someone who thrives at the intersection of biology, computation, product strategy, and engineering execution
• Bachelor's/ Master's degree in relevant field (computational biology, bioinformatics, systems biology, computer science) or equivalent relevant education and experience
• 6+ years industry experience in computational biology or data-driven discovery; minimum 1 years’ experience in software engineering and data engineering teams
• Proficiency working with programming languages Python, and R, modern development frameworks and developing internal packages
• Experience with omics/translational data analysis, scalable ETL pipelines, data modeling, and associated QC
• 1+ years’ experience leading complex projects as product owner
• Experience supporting target identification, prioritization, or multi-modal analysis

Desirable

• We are seeking an exceptional Staff Computational Biologist to drive the next generation of software and data products supporting Target Identification and Prioritization across our research organization
• As a senior member of the Translational Platform Engineering team, you will act as a product owner, technical strategist, and rapid prototyper, responsible for shaping the roadmap and delivering tools that power discovery teams
• Your day to day includes working with biology data scientists to harden their notebooks and workflows, pushing new releases to production (on a predictable schedule), and sitting with biologists and chemists as they use the UIs to advance our translational biology efforts
• The Staff Computational Biologist is the key to translating use cases into technical specifications for engineering teams
• This is a highly visible and impactful role where you will contribute to a human-biology-first approach to drug discovery programs by leading the end-to-end lifecycle of platform capabilities used daily by our Target ID scientists
• Own the product roadmap for Target ID software
• Gather and prioritize scientific requirements from internal users
• Translate use cases into technical specifications for engineering teams
• Rapidly prototype computational solutions using Python
• Develop and maintain internal packages, reproducible workflows, and APIs
• Establish documentation, onboarding materials, and best practices for internal platform usage
• Lead cross-functional project execution (data engineering, software engineering)
• Follow good engineering practices (i.e. CI/CD, predictable demo cadence, etc.)