Valo Health

<div><h3>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&amp;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/" rel="noopener noreferrer ugc" target="_blank">www.valohealth.com</a>.  </div><h4>About the Role</h4>
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…
<ul>
<li>Own the product roadmap for Target ID software.</li>
<li>Gather and prioritize scientific requirements from internal users.</li>
<li>Translate use cases into technical specifications for engineering teams.</li>
<li>Rapidly prototype computational solutions using Python.</li>
<li>Develop and maintain internal packages, reproducible workflows, and APIs.</li>
<li>Establish documentation, onboarding materials, and best practices for internal platform usage.</li>
<li>Lead cross-functional project execution (data engineering, software engineering).</li>
<li>Follow good engineering practices (i.e. CI/CD, predictable demo cadence, etc.)</li>
</ul>
What You Bring...
<ul>
<li>Bachelor's/ Master's degree in relevant field (computational biology, bioinformatics, systems biology, computer science) or equivalent relevant education and experience</li>
<li>6+ years industry experience in computational biology or data-driven discovery; minimum 1 years’ experience in software engineering and data engineering teams</li>
<li>Proficiency working with programming languages Python, and R, modern development frameworks and developing internal packages</li>
<li>Experience with omics/translational data analysis, scalable ETL pipelines, data modeling, and associated QC</li>
<li>1+ years’ experience leading complex projects as product owner</li>
<li>Experience supporting target identification, prioritization, or multi-modal analysis.</li>
</ul>
Nice to have...
<ul>
<li>Experience with dashboard development (e.g. Shiny, Dash, Streamlit, React, Veu.js).</li>
<li>Understanding of cloud-native tools and modern data platforms (AWS/GCP/Azure).</li>
<li>Familiarity with the drug discovery and development process is a plus</li>
</ul>
 <div><div><div>Remote Salary Range</div><div>$165,750—$195,000 USD</div></div><div><div>CA Salary Range</div><div>$195,585—$230,100 USD</div></div></div><div>
<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>

Staff Data Scientist, Computational Biology

<div><h3>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&amp;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/" rel="noopener noreferrer ugc" target="_blank">www.valohealth.com</a>.  </div>About the Role...
As a Staff Data Scientist, Machine Learning in Epidemiology and Patient Data Products, you will be a core member on a team of data scientists building a powerful computational platform for advancing the discovery and development of new medicines. In this role, you will develop machine learning tools for patient data and drive their adoption across teams, under the guidance of epidemiology and biology program leads. Successful candidates will work with a diverse group of scientists and domain experts, in ways that cut across traditional industry boundaries in an innovative startup environment.
What You’ll Do… 
Your primary areas of responsibility will be:  
<ul>
<li>As a senior member of our team, you will lead the development of machine learning (ML) methods and analyses of patient data with diverse stakeholders. For example, integrate clinical insights into supervised and unsupervised learning approaches and generate patient profiles.</li>
<li>Perform project-specific hands-on analysis and modeling of high-dimensional longitudinal real-world data, spanning electronic medical records (EHRs), clinical notes, sequencing data, and multi-omics, using modern data science tools in cloud environments.</li>
<li>Contribute to the design, implementation, and evaluation of innovative machine learning approaches for patient data to provide novel clinical insights.</li>
<li>Be comfortable with scientific uncertainty and embrace curiosity and creative solutions. Many of the challenges we tackle don’t have known solutions or established pathways.</li>
<li>Use your technical knowledge and intuition to articulate and break down large problems into solvable pieces. There are a lot of problems to solve; you’ll need to prioritize which of these are critical-path today from those that can wait.</li>
<li>Be a dynamic and active team member, championing shared coding standards, participating in code reviews, and providing regular updates on your work and input into the work of your colleagues.</li>
</ul>
What You Bring… 
<ul>
<li>MS, MPH, or PhD in health data science, biostatistics, or a related quantitative field, with 5 years of experience developing and applying ML methods, including at least 3 years working directly with real-world patient data. Experience in a biopharmaceutical, epidemiological or biostatistical setting is a plus.</li>
<li>Extensive experience developing and implementing machine learning solutions in healthcare databases, including EHRs, administrative claims, and patient registries. Familiarity with U.S. and global medical coding ontologies and data models (ICD, ATC, LOINC, SNOMED, CPT, HCPCS, OMOP, etc.). Confident working with highly sparse and high-dimensional data. Experience processing and mining clinical notes is a plus.</li>
<li>Extensive experience building, maintaining, and operationalizing ML pipelines, and translating model outputs into meaningful insights for diverse audiences.</li>
<li>Broad proficiency across core ML paradigms (e.g., supervised, unsupervised, semi-supervised) and experience with linear and logistic regression, classification and tree‑based methods, clustering and dimensionality‑reduction techniques, and deep learning architectures. Hands-on experience with representation learning and transformer-based and other sequence models is a plus.</li>
<li>Strong grounding in key components of the ML development lifecycle, including evaluation metrics, hyperparameter tuning, model selection, feature engineering and selection, model explainability, and MLOps best practices.</li>
<li>Mastery of Python and modern data science tools (e.g., scikit-learn, PyTorch, statsmodels, SciPy, MLlib, MLflow). Experience with AI-assisted coding tools (e.g., Claude Code) is a plus.</li>
<li>Comfortable working in ambiguous problem spaces; experience working in a start-up or agile work environment as part of cross-functional project teams.</li>
<li>Ability to lead and facilitate meetings and work collaboratively on multi-disciplinary project teams.</li>
<li>Exceptional time management, ability to prioritize multiple tasks simultaneously, and deliver products on time every time.</li>
<li>Enthusiastic about documentation–ensuring that all analyses are clear and reproducible with thorough documentation of key assumptions and decision points.</li>
</ul>
You May Also Bring…
<ul>
<li>Advanced knowledge of biostatistics approaches, including inferential and predictive modeling. Experience in causal approaches for observational studies, including propensity score methods, bias adjustment, and covariate selection and adjustment.</li>
<li>Familiarity with or exposure to traditional drug discovery and development processes and approaches.</li>
</ul><div><div><div>Remote Salary Range</div><div>$165,000—$190,000 USD</div></div><div><div>CA Salary Range</div><div>$175,000—$220,000 USD</div></div></div><div>
<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>

Valo Health

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Staff Data Scientist, Computational Biology

Staff Data Scientist, Machine Learning in Epidemiology and Patient Data Products

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