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Staff Data Scientist, Graph ML

May 9, 2026

<div class="content-intro"><h3 class="x_MsoNormal">About Us</h3> 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 <a href="http://www.valohealth.com/" data-outlook-id="5b38894b-e5d7-4841-bcf8-af9440ad7230" data-auth="NotApplicable" data-linkindex="0">www.valohealth.com</a>.  </div>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… <ul> <li> Lead the design, implementation and application of graph ML and network biology approaches to target discovery from RWD and multi-omic datasets.</li> <li>Prototype new approaches aimed at enhancing and improving Valo’s graph platform, seeking out new scientific opportunities to increase the team’s impact.</li> <li>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.</li> <li>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.</li> <li> 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.</li> </ul> What You Bring… <ul> <li> MS or PhD in a quantitative field with extensive experience at the intersection of machine learning and graph analytics</li> <li> Experience in healthcare, medicine, molecular biology, computational biology, or life sciences.</li> <li> 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</li> <li>Experience or general knowledge of knowledge-graph building and graph databases</li> <li> Familiarity with general graph algorithms and relevant Python libraries</li> <li>Strong experience in Python and machine learning and/or deep-learning frameworks (e.g., pytorch)</li> <li>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)</li> <li>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.</li> </ul> Nice to have… <ul> <li> Experience with traditional drug discovery and development processes and approaches</li> <li>Domain expertise in neuroscience, immunology, and/or cardio-metabolic biology</li> <li> Knowledge of related data science domains, including statistical genetics, multi-omics & real-world evidence </li> </ul><div class="content-pay-transparency"><div class="pay-input"><div class="title">Remote Salary Range</div><div class="pay-range">$200,600—$236,000 USD</div></div><div class="pay-input"><div class="title">MA Salary Range</div><div class="pay-range">$170,000—$200,000 USD</div></div></div><div class="content-conclusion"> <h3></h3> <h3></h3> 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. </div>

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Common Interview Questions And Answers

1. HOW DO YOU PLAN YOUR DAY?

This is what this question poses: When do you focus and start working seriously? What are the hours you work optimally? Are you a night owl? A morning bird? Remote teams can be made up of people working on different shifts and around the world, so you won't necessarily be stuck in the 9-5 schedule if it's not for you...

2. HOW DO YOU USE THE DIFFERENT COMMUNICATION TOOLS IN DIFFERENT SITUATIONS?

When you're working on a remote team, there's no way to chat in the hallway between meetings or catch up on the latest project during an office carpool. Therefore, virtual communication will be absolutely essential to get your work done...

3. WHAT IS "WORKING REMOTE" REALLY FOR YOU?

Many people want to work remotely because of the flexibility it allows. You can work anywhere and at any time of the day...

4. WHAT DO YOU NEED IN YOUR PHYSICAL WORKSPACE TO SUCCEED IN YOUR WORK?

With this question, companies are looking to see what equipment they may need to provide you with and to verify how aware you are of what remote working could mean for you physically and logistically...

5. HOW DO YOU PROCESS INFORMATION?

Several years ago, I was working in a team to plan a big event. My supervisor made us all work as a team before the big day. One of our activities has been to find out how each of us processes information...

6. HOW DO YOU MANAGE THE CALENDAR AND THE PROGRAM? WHICH APPLICATIONS / SYSTEM DO YOU USE?

Or you may receive even more specific questions, such as: What's on your calendar? Do you plan blocks of time to do certain types of work? Do you have an open calendar that everyone can see?...

7. HOW DO YOU ORGANIZE FILES, LINKS, AND TABS ON YOUR COMPUTER?

Just like your schedule, how you track files and other information is very important. After all, everything is digital!...

8. HOW TO PRIORITIZE WORK?

The day I watched Marie Forleo's film separating the important from the urgent, my life changed. Not all remote jobs start fast, but most of them are...

9. HOW DO YOU PREPARE FOR A MEETING AND PREPARE A MEETING? WHAT DO YOU SEE HAPPENING DURING THE MEETING?

Just as communication is essential when working remotely, so is organization. Because you won't have those opportunities in the elevator or a casual conversation in the lunchroom, you should take advantage of the little time you have in a video or phone conference...

10. HOW DO YOU USE TECHNOLOGY ON A DAILY BASIS, IN YOUR WORK AND FOR YOUR PLEASURE?

This is a great question because it shows your comfort level with technology, which is very important for a remote worker because you will be working with technology over time...