Valo Health is looking to revolutionize drug discovery by leveraging AI and real-world data to accelerate the development of new medicines, specifically addressing challenges in neurodegenerative disease research.
Requirements
Robust statistical analytic skills, applicable to observation study designs, including cohort/longitudinal studies of electronic health records/real world data.
Advanced knowledge in biostatistics approaches, including inferential and predictive modeling, and comfortable incorporating causal inference techniques with machine learning algorithms in real world data.
Familiarity with applying LLMs to real world data for data curation and extracting insights.
Must have experience conducting data manipulation and statistical analysis in Python and/or R programming languages.
Responsibilities
As a senior member of our neurodegenerative disease drug discovery team, you will lead complex research projects from conceptualization through execution, that incorporate multiple workstreams stemming from real-world data studies (e.g., electronic medical records) for projects in drug discovery and development.
Provide mentorship and oversee technical members of our Epidemiology and Patient Data team. In addition, Principal roles consult on partner teams, providing technical expertise across translational data science (e.g., knowledge graph, statistical genetics, computational biology).
Be a project leader, engage external partners and stakeholders to translate research questions into observational study designs, implement project plans that prioritize high impact workstreams for clients, and leverage your medical domain knowledge to create deliverables that showcase patient-centric insights that resonate with diverse audiences.
Collaborate with data science and program management functions to define project scope, establish timelines, and allocate resources. Leverage agile software tools (e.g., Jira boards) to manage complex projects and timelines across multiple workstreams.
Work with a diverse array of global patient data spanning electronic medical records, sequencing, multi-omics data, and other data modalities using R and Python in cloud environments.
Be an active team member, championing and adopting shared analytic and coding standards.
Other
PhD in epidemiology or biostatistics with 7+ years of work-related experience (or MPH/MS with 10+ years)leading epidemiological, statistical, and/or machine learning projects in real-world patient data.
Clear communication and confidence in your ability to use agile software tools (e.g., Jira boards) to implement project plans and manage timelines (e.g., Gantt charts) used by multiple teams.
Experience leading complex research projects with real business impacts: from co-creating research programs with clients to delivering high-impact insights to leadership.
Experience being an externally facing project leader, leading meetings, and soliciting input from clients, and keeping relevant stakeholders in the loop to ensure alignment throughout project lifecycle.
Comfortable working in ambiguous problem spaces; experience working in a start-up or agile work environment as part of cross-functional project teams.
At this time, we are only able to consider candidates who currently have permanent US work authorization without the need for immediate or future sponsorship.
