About Us

Valo Health is a human-centric, AI-enabled biotechnology company working to make new drugs for patients faster. The company’s Opal Computational Platform transforms drug discovery and development through a unique combination of real-world data, AI, human translational models and predictive chemistry. 

Our talented team of biologists, chemists and engineers, armed with advanced AI/ML tools, work together to break down traditional R&D silos and accelerate the speed and scale of drug discovery and development. 

Valo is committed to hiring diverse talent, prioritizing growth and development, fostering an inclusive environment, and creating opportunities to bring together a group of different experiences, backgrounds, and voices to work together. We embrace new ways of learning, solve complex problems and welcome diverse perspectives that can help us advance patient-centric innovation. 

Valo is headquartered in Lexington, MA, with additional offices in New York, NY and Tel Aviv, Israel.  To learn more, visit www.valohealth.com.  

About the Role

As a Staff Data Scientist in Computational Biology, you will be part of the target prioritization team responsible for delivering strong target candidates and accelerating drug preclinical programs.  You will lead the strategy for data integration, target prioritization and execution in the immune-cardio-metabolic therapeutic area, applying innovative solutions to multi-dimensional data to define the best targets, and move them forward. You will closely collaborate with discovery scientists, data scientists, epidemiologists, and engineers to maximize the generation of actionable insights and target hypotheses from our internal datasets, while applying creative computational approaches to address critical scientific questions while contributing to Valo’s platform. 
  
A successful candidate will have the ability to work and communicate with a diverse set of scientists, and domain experts in synergistic ways, closing the gap between experimental and data scientists, and across different teams. You will be driven by scientific curiosity and have a deep intuition and understanding of biological systems. You will be comfortable with the uncertainty inherent to scientific research and be willing to learn while paving the path to new approaches.

What You'll Do...

• Lead the development of target prioritization strategy and execution, incorporating cell-specific information through interpretable machine learning models in the immune-cardio-metabolic therapeutic area.
• Contribute to the analyses and integration of scRNAseq datasets within interpretable machine learning models aimed at target discovery and prioritization.
• Collaborate with other data scientists to improve and expand the applications of our computational platform.
• Engage with discovery stakeholders to come up with novel approaches that better capture our scientific strategy, while supporting new hypotheses and/or research questions.
• Support external partnerships by aligning strategically with partners and meeting delivery expectations.
• Be a curious, agile and pro-active team member, providing regular updates of your work and looking for new scientific opportunities within the team.

What You Bring... 

• PhD + 5 years experience in computational sciences, computational biology, or related fields (e.g., systems biology, genetics, molecular biology, physics) in collaborative settings to unravel complex biological questions and communicate domain knowledge to non-computational stakeholders & colleagues.

• Experience in scRNAseq analyses and computational approaches using modern computational methods towards understanding cellular pathways, cell transition states, and holistic disease processes. 

• Strong analytical, problem-solving, and communication skills.
• Demonstrated experience in modern data science toolkits, including python, R, github/gitlab towards building reproducible analytical processes.
• Ability to condense, summarize, and synthesize results into informative and actionable presentations to scientific audiences as demonstrated by original peer-reviewed publications in respected journals, oral presentations at scientific meetings.  

• Experience in documenting computational projects, code, data, and model versioning.
• Ability to multi-task and work in fast-paced environments.

Nice to have:

• Experience in systems biology approaches to derive insights from multi-dimensional data.
• Experience in cellular mixture deconvolution approaches, with a focus on immune system.
• Experience in interpretable machine learning models.
• Experience in multi-omics approaches and data (2 or more: genomic, transcriptomic, proteomic, and/or metabolomic) using computational biology methods towards understanding holistic disease processes.
• Domain knowledge in immune-cardio-metabolic therapeutic area.

Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Valo Health currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Valo Health's good faith estimate as of the date of publication and may be modified in the future.

Please note: 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.