About the Role

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. This hybrid role is ideal for someone who thrives at the intersection of biology, computation, product strategy, and engineering execution.

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.

What You’ll Do…

• 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.)

What You Bring...

• 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.

Nice to have...

• Experience with dashboard development (e.g. Shiny, Dash, Streamlit, React, Veu.js).
• Understanding of cloud-native tools and modern data platforms (AWS/GCP/Azure).
• Familiarity with the drug discovery and development process is a plus

About the Role...  

Valo is looking for a Scientist II to play a pivotal role in wet-lab target validation and assay development for neurodegenerative disease targets, with an initial focus on Parkinson’s disease, that have been identified using Valo’s human-centric Opal computational platform.  This role will also support drug discovery program goals including compound and biological mechanism of action and cellular efficacy model studies.   

 The Scientist II will have a passion for translating human data insights into new therapies for complex neurodegenerative diseases.  The Scientist II will work cross-functionally with subject matter experts, computational scientists, and engineers in a team-based environment to bring forward novel and creative solutions to target validation.   Your work will build confidence in the translation of candidate drug targets to diseases of interest.  You will also develop assays to characterize and address specific questions related to drug development of selected targets 

As a key bench scientist, you will execute experiments to deliver validation data packages, and present results to internal and external stakeholders. This work will be done with a high degree of reliability, efficiency, and accuracy to allow key decisions on Valo targets.  

What You’ll Do…   

Your primary areas of responsibility will be:     

• Generate experimental plans and execute at the bench to enable validation of novel therapeutic targets, address biological questions related to target drug discovery, and inform compound mechanism of action  

• Develop and build well controlled human functional cellular assays in neuronal, glia, and other CNS relevant cell types to enable characterization of novel drug targets   

• Perform experiments and generate data in the laboratory with a high degree of reliability, efficiency, and accuracy to support target validation projects.   

• Work in collaboration with other Valo scientists to progress target validation and drug development aligned with company goals  
  
  
• Generate data with high quality standards and document within an electronic lab notebook  
  
  
• Stay current on emerging trends and advancements in the field   

What You Bring…   

• A PhD in Biological Sciences or a related field with 2+ years of experience (or MS with 6+ years of experience or a BS with 8+ years of experience)  

• Expertise in one or more of the following areas: Neurobiology, Neurodegenerative disease, Parkison’s disease, cell biology  

• Expertise in neuronal and neurodegenerative disease models (e.g. experience with PFF seeding models (α–synuclein) and iPSC dopaminergic neuronal culture)  

• Experience in human in vitro systems including primary cell culture and iPSC differentiation with neuronal cell types (neurons, microglia, astrocytes, co-culture systems), molecular biology, and genetic manipulation (CRISPR, siRNA, overexpression systems)  

• Experience in assay development with functional readouts (neuronal function, cell death assay, phagocytosis, cellular function and morphology, western blotting, ELISA, imaging (ICC/IF), qPCR/RT-qPCR)  

• Strong oral and written communication, presentation and interpersonal skills    

• Track record of impactful scientific contributions as demonstrated by high impact publications   
  
  
• Experience collaborating with multidisciplinary teams   

You May Also Bring…    

• Experience in human in vitro systems including cell culture and functional assays related to Parkinson’s disease  

• Experience with organoids or 2D/3D models  

• Experience with barrier models looking at BBB structure and function  

• Experience working in in vivo/ex vivo systems   

• Experience in discovery stage preclinical drug discovery programs and with target validation projects   

About the Role...  

Valo is looking for a Scientist I to play a pivotal role in the experimental validation of targets for Parkinson’s disease, and other neurodegenerative diseases, that have been identified using Valo’s human-centric Opal computational platform. This role will also support drug discovery program goals including compound mechanism of action.  

The Scientist I will have a passion for translating human data insights into new therapies for complex neurodegenerative diseases.  The Scientist I will work cross-functionally with subject matter experts, computational scientists, and engineers in a team-based environment to bring forward novel and creative solutions to target validation. 

You will bring your experience in immune and inflammatory mechanisms and models to design and execute target validation experiments using human cell assays.  The work you do will build confidence in the translation of candidate drug targets to diseases of interest.  

As a hands-on experimentalist, you will execute at the bench with a high degree of reliability, efficiency, and accuracy and deliver validation data packages, data interpretations, and present results to appropriate stakeholders. 

What You’ll Do…   

Your primary areas of responsibility will be:    

• Generate experimental plans and execute at the bench to enable validation of novel therapeutic targets   

• Develop and execute human functional cell-based assays in immune and neuroinflammatory cell types to enable characterization of novel drug targets  

• Perform experiments and generate data in the laboratory with a high degree of reliability, efficiency, and accuracy to support target validation projects.  

• Work in collaboration with other Valo scientists to progress target validation and drug development aligned with company goals 

• Generate data with high quality standards and document within an electronic lab notebook  
  
  
• Stay current on emerging trends and advancements in the field  

What You Bring…   

• A PhD in Biological Sciences or a related field with 0-2+ years of experience (or MS with 4+ years of experience or a BS with 6+ years of experience)  

• Expertise in one or more of the following areas: Immunology, Autoimmune Disease, Neuroimmunology, Neuroinflammation 

• This position requires experience in immune and inflammatory mechanisms and models.  

• Experience in human in vitro systems including direct cell culture with immune cell types (e.g. PMBCs, blood-based cancer cell lines, iPSCs derived immune cells), molecular biology, and genetic manipulation 

• Experience in assay development with functional readouts (cytokine profiling, inflammatory signaling, flow cytometry, phagocytosis, cell death assay, cellular function) 

• Strong oral and written communication, presentation and interpersonal skills   

• Track record of impactful scientific contributions as demonstrated by high impact publications  
  
  
• Experience collaborating with multidisciplinary teams 

You May Also Bring…    

• Experience in human in vitro systems including cell culture and functional assays involving neuroinflammatory cells and/or neurons 

• Experience working in in vivo/ex vivo systems  

• Experience in discovery stage preclinical drug discovery programs and with target validation projects  

Staff Data Scientist, Graph ML

About Us Valo Health is a technology company applying human and machine intelligence to accelerate the creation of life-changing medical treatments. At the core of this vision is Valo’s computational platform: an end-to-end, integrated drug discovery and development engine built from the ground up. Valo hires the best and gives them first-class training and support. We approach our work fearlessly, learn quickly, improve constantly, and celebrate our wins. A centerpiece of our culture is our commitment to inclusion across race, gender, age, religion, identity, and experience. Diversity fuels the Valo experience and drives us every day. We strive to create an inclusive workplace that cultivates bold innovation through collaboration and empowers our people to unleash their full potential.

As Staff Data Scientist, Graph ML, you will develop and deploy graph ML solutions to synthesize and extract novel insights from Valo data in the context of a vast corpus of knowledge in medicine, molecular biology, human genetics, and drugs, to drive compute-enabled biological hypothesis generation. Our innovative platform leverages advanced computational techniques, starting with patient data, to bring better medicines to patients, faster. You will be responsible for developing and delivering graph ML and network biology-based analyses that generate and support drug target hypotheses on the path to discovery of new medicines. You will collaborate closely with a diverse group of data scientists and biologists to enable the contextualization of predicted drug targets within relevant patient subpopulations. You will also be accountable for communicating methodological approaches and key results to internal and external cross-functional stakeholders. Additionally, you will work with other data scientists, software engineers, and data engineers to continue building and improving Valo’s integrated graph platform to accelerate insights across multiple projects and applications.

A successful candidate brings deep technical expertise in graph machine learning, network analytics, and modern data science best practices, along with experience in biology research in the context of drug discovery, and curiosity and excitement to learn.

What You’ll Do…

•  Lead the design, implementation and application of graph ML and network biology approaches to target discovery from RWD and multi-omic datasets.
• Prototype new approaches aimed at enhancing and improving Valo’s graph platform, seeking out new scientific opportunities to increase the team’s impact.
• Work with world-class engineers to ensure that graph methodologies, graph construction, and underlying data are robustly integrated, to develop generalizable solutions to core scientific problems.
• Apply your technical knowledge and intuition to 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.
•  Be an agile and pro-active Data Science team member, providing regular updates on 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 extensive experience at the intersection of machine learning and graph analytics
•  Experience in healthcare, medicine, molecular biology, computational biology, or life sciences.
•  Advanced knowledge of and 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 machine learning and/or deep-learning frameworks (e.g., pytorch)
• Experience with data science best practices (data provenance, code versioning, reproducibility, git, etc), large-scale data analytics engines (e.g., Spark or Dask), and working in cloud environments (e.g., AWS)
• Strong data visualization, analytical, problem-solving, and communication skills, with demonstrated ability to condense, summarize, and synthesize results into informative and actionable presentations to experts from different fields.

Nice to have…

•  Experience with traditional drug discovery and development processes and approaches
• Domain expertise in neuroscience, immunology, and/or cardio-metabolic biology
•  Knowledge of related data science domains, including statistical genetics, multi-omics & real-world evidence