Valo Health is a technology company that is integrating human-centric data and AI-powered technology to accelerate the creation of life-changing drugs for more patients faster. Valo was created with the belief that the drug discovery and development process can and should be faster and less expensive, with a much higher probability of success. We are using models early to fail less often, executing clinical trials to add valuation to the company, and generating fit-for-purpose data to feed back into Valo's Opal Computational Platform as we reinvent drug discovery and development from the ground up. Disease doesn't wait, so neither can we.We are a multi-disciplinary team of experts in science, technology, and pharmaceuticals united in our mission to achieve better drugs for patients faster. 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 achieve the widest-ranging impact when we leverage our broad backgrounds and perspectives to accelerate a new frontier in health. Valo seeks to become the catalyst for the pharmaceutical industry and drive the digital transformation of the industry. Are you ready to join us?As aStaff Data Scientist, Machine Learning , you will be a core member of a team of data scientists and engineers building a powerful computational platform for advancing the research and development of new medicines. As part of the Translational Data Science team, you will help design, develop, and apply machine learning (ML) models, methods, and pipelines for scientific problems involving clinical and biomedical data. Successful candidates will work with a diverse set of data scientists, biological scientists, epidemiologists, and software engineers in ways that cut across traditional industry boundaries.What You'll Do...Perform hands-on exploratory and defined analysis and modeling of high-dimensional longitudinal data to generate fit-for-purpose evidence for decision making for multiple projects.Design and implement innovative ML approaches leveraging Valo's proprietary platform (data assets and data science packages) as well as newly published methods.Contribute to the design and implementation of robust, automated pipelines leveraging deep learning and classical ML on high dimensional electronic health records and omics data to solve scientific problems.Develop well-designed, tested, and documented software packages.Contribute to planning, execution, interpretation, and communication of results.Collaborate with cross-functional teams and key stakeholders to derive user requirements, maintain alignment, and ensure the relevance and impact of models, analyses, and pipelines.Be an active team member in code, design, and analysis review.What You Bring...Degree in a quantitative field with the following years of post-degree experience or equivalent oBS: 7+; MS: 5+; PhD: 3+Broad experience in ML including random forest, logistic regression, dimensionality reduction, clustering, metrics, model selection, features election, and explainability (3+ years required).Demonstrated experience implementing and applying deep learning approaches such as representation learning, sequence models, transformers, and self-supervised learning on high dimensional or multimodal data (2+ years required).Proficient in Python (3+ years required) and experience with ML, deep learning, and data science packages (e.g., scikit-learn, pytorch, stats models, scipy, MLlib).Experience with collaborative software development using source control). management (e.g., git, unit testing, code review, CI/CD) (2+ years required)Experience with MLops methodology such as workflow orchestration (e.g.,Airflow, Prefect), experiment tracking (e.g., MLflow), containerization (e.g.,Docker), and reproducible research (1+ years required).Experience with ML on electronic health records (1+ years required).Experience with large-scale data analytics engines (e.g., Spark or Dask) and working in cloud environments (e.g., AWS).Experience with statistical methods such as hypothesis testing, longitudinal modeling, and time to event analysis.Strong work ethic with a bias for execution and an ability to manage multiple priorities, ambiguity, and tight timelines.Ability to work effectively in teams or independently.Experience with omics data is a plus.Familiarity with the drug discovery and development process is a plus.SalaryNew York Base Salary: $192,780 to $203,900San Francisco Base Salary: $200,000 to $227,000This range represents the low and high end of the anticipated annual base salary range for the New York City based and San Francisco based position. The actual annual base salary will depend on numerous factors such as: experience, knowledge, skills, and if the location of the job changes.More on ValoValo Health, Inc ('Valo') is a technology company built to transform the drug discovery and development process using human-centric data and artificial intelligence-driven computation. As a digitally native company, Valo aims to fully integrate human-centric data across the entire drug development life cycle into a single unified architecture, thereby accelerating the discovery and development of life-changing drugs while simultaneously reducing costs, time, and failure rates. The company's Opal Computational Platform is an integrated set of capabilities designed to transform data into valuable insights that may accelerate discoveries and enable Valo to advance a robust pipeline of programs across cardiovascular metabolic renal, oncology, and neurodegenerative disease. Founded by Flagship Pioneering and headquartered in Boston, MA, Valo also has offices in Lexington, MA, and New York. To learn more, visit www.valohealth.com.#J-18808-Ljbffrby Jobble

Valo Health is a technology company that is integrating human-centric data and AI-powered technology to accelerate the creation of life-changing drugs for more patients faster. Valo was created with the belief that the drug discovery and development process can and should be faster and less expensive, with a much higher probability of success. We are using models early to fail less often, executing clinical trials to add valuation to the company, and generating fit-for-purpose data to feed back into Valo's Opal Computational Platform™ as we reinvent drug discovery and development from the ground up. Disease doesn't wait, so neither can we. We are a multi-disciplinary team of experts in science, technology, and pharmaceuticals united in our mission to achieve better drugs for patients faster. 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 achieve the widest-ranging impact when we leverage our broad backgrounds and perspectives to accelerate a new frontier in health. Valo seeks to become the catalyst for the pharmaceutical industry and drive the digital transformation of the industry. Are you ready to join us? As a Staff Data Scientist, Machine Learning, you will be a core member of a team of data scientists and engineers building a powerful computational platform for advancing the research and development of new medicines. As part of the Translational Data Science team, you will help design, develop, and apply machine learning (ML) models, methods, and pipelines for scientific problems involving clinical and biomedical data. Successful candidates will work with a diverse set of data scientists, biological scientists, epidemiologists, and software engineers in ways that cut across traditional industry boundaries. What You'll Do... <ul><li>Perform hands-on exploratory and defined analysis and modeling of high-dimensional longitudinal data to generate fit-for-purpose evidence for decision making for multiple projects.</li><li>Design and implement innovative ML approaches leveraging Valo's proprietary platform (data assets and data science packages) as well as newly published methods.</li><li>Contribute to the design and implementation of robust, automated pipelines leveraging deep learning and classical ML on high dimensional electronic health records and omics data to solve scientific problems.</li><li>Develop well-designed, tested, and documented software packages.</li><li>Contribute to planning, execution, interpretation, and communication of results.</li><li>Collaborate with cross-functional teams and key stakeholders to derive user requirements, maintain alignment, and ensure the relevance and impact of models, analyses, and pipelines.</li><li>Be an active team member in code, design, and analysis review.</li></ul> What You Bring... <ul><li>Degree in a quantitative field with the following years of post-degree experience or equivalent oBS: 7+; MS: 5+; PhD: 3+</li><li>Broad experience in ML including random forest, logistic regression, dimensionality reduction, clustering, metrics, model selection, features election, and explainability (3+ years required).</li><li>Demonstrated experience implementing and applying deep learning approaches such as representation learning, sequence models, transformers, and self-supervised learning on high dimensional or multimodal data (2+ years required).</li><li>Proficient in Python (3+ years required) and experience with ML, deep learning, and data science packages (e.g., scikit-learn, pytorch, stats models, scipy, MLlib).</li><li>Experience with collaborative software development using source control). management (e.g., git, unit testing, code review, CI/CD) (2+ years required)</li><li>Experience with MLops methodology such as workflow orchestration (e.g.,Airflow, Prefect), experiment tracking (e.g., MLflow), containerization (e.g.,Docker), and reproducible research (1+ years required).</li><li>Experience with ML on electronic health records (1+ years required).</li><li>Experience with large-scale data analytics engines (e.g., Spark or Dask) and working in cloud environments (e.g., AWS).</li><li>Experience with statistical methods such as hypothesis testing, longitudinal modeling, and time to event analysis.</li><li>Strong work ethic with a bias for execution and an ability to manage multiple priorities, ambiguity, and tight timelines.</li><li>Ability to work effectively in teams or independently.</li><li>Experience with omics data is a plus.</li><li>Familiarity with the drug discovery and development process is a plus.</li></ul> Salary <ul><li>New York Base Salary: $192,780 to $203,900</li><li>San Francisco Base Salary: $200,000 to $227,000</li></ul> This range represents the low and high end of the anticipated annual base salary range for the New York City based and San Francisco based position. The actual annual base salary will depend on numerous factors such as: experience, knowledge, skills, and if the location of the job changes. More on Valo Valo Health, Inc ("Valo") is a technology company built to transform the drug discovery and development process using human-centric data and artificial intelligence-driven computation. As a digitally native company, Valo aims to fully integrate human-centric data across the entire drug development life cycle into a single unified architecture, thereby accelerating the discovery and development of life-changing drugs while simultaneously reducing costs, time, and failure rates. The company's Opal Computational Platform™ is an integrated set of capabilities designed to transform data into valuable insights that may accelerate discoveries and enable Valo to advance a robust pipeline of programs across cardiovascular metabolic renal, oncology, and neurodegenerative disease. Founded by Flagship Pioneering and headquartered in Boston, MA, Valo also has offices in Lexington, MA, and New York. To learn more, visit www.valohealth.com.

Location: New York City or Remote USA About Us Valo Health is a technology company that is integrating human-centric data and AI-powered technology to accelerate the creation of life-changing drugs for more patients faster. Valo was created with the belief that the drug discovery and development process can and should be faster and less expensive, with a much higher probability of success. We are using models early to fail less often, executing clinical trials to add valuation to the company, and generating fit-for-purpose data to feed back into Valo's Opal Computational Platform™ as we reinvent drug discovery and development from the ground up. Disease doesn't wait, so neither can we. We are a multi-disciplinary team of experts in science, technology, and pharmaceuticals united in our mission to achieve better drugs for patients faster. 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 achieve the widest-ranging impact when we leverage our broad backgrounds and perspectives to accelerate a new frontier in health. Valo seeks to become the catalyst for the pharmaceutical industry and drive the digital transformation of the industry. Are you ready to join us? About the Role As a Senior Clinical Informatics Data Scientist, you will be a core member of a team of data scientists and engineers building a powerful computational platform for advancing the discovery and development of new medicines. In this role, you will develop solutions and execute complex initiatives that leverage real-world data (e.g., electronic medical records, biomedical imaging, time-series data, surveys/questionnaires, and text notes) to address challenging computational problems alongside partner scientists in epidemiology, statistical genetics, computational biology, and machine learning. Successful candidates will work with a diverse set of scientists, and domain experts in ways that cut across traditional industry boundaries in an innovative startup environment. What You'll Do... <ul><li>Develop clinical concepts, medical code mappings, and data dictionaries for real-world data types. Maintain data dictionaries used by partner teams and external clients to facilitate high-quality data analysis.</li><li>Define and implement data harmonization standards and curation strategies for real-world patient data products, including data mapping, cleaning and automating ETL pipelines across various data sources.</li><li>Lead the development and maintenance of user-driven tools/packages to generalize data processes and automate data transformation in real-world data studies and machine learning projects. Seek out opportunities to improve these tools/packages from user feedback.</li><li>Collaborate with pre-clinical data science and clinical teams to define data requirements, reconciling research needs with real-world data collection practices and utilization.</li><li>Contribute to writing reports and presentations to non-technical internal audiences and external clients.</li><li>Work in an agile manner to create high-quality, analysis-ready data sets and products to be used across the organization.</li><li>Use your technical knowledge and intuition to articulate and 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 a dynamic and active team member, championing and adopting shared coding standards, participating in code review, and providing regular updates of your work and input into the work of your colleagues.</li></ul>What You Bring... <ul><li>Bachelor's with 5+ years or MS / PhD with 1+ years in a medically-related field with a quantitative focus (public health, health economics, biostatistics) or in in a quantitative field (computer science, statistics, computational biology, biomedical engineering).</li><li>Must have 3+ years of experience working with real world data, clinical trial data and/or preclinical data. Practical experience in data cleaning, filtering, and harmonizing real world patient data, and conducting quality and capability evaluations.</li><li>Must have experience developing and maintaining healthcare data dictionaries for patient data.</li><li>Knowledge of medical coding ontologies and data models for real-world data types in US and globally (ICD, ATC, LOINC, SNOMED, CPT, HCPCS, etc).</li><li>Fluency in Python (required) and relevant data science packages (e.g. pandas). Experience in R and SQL a plus.</li><li>Familiarity and/or experience with Spark (pyspark) including performance optimization through query techniques, data storage techniques, or configuration tuning.</li><li>Familiarity and/or experience with cloud computing (AWS), Linux environments, and shell scripting.</li><li>Familiarity and/or experience with SQL connectors (e.g. Snowflake), and unstructured/text analysis (e.g. regular expressions, NLTK, spaCy/medspaCy) a plus. </li><li>Familiarity and/or experience with designing python libraries or packages in other languages is a plus.</li><li>Familiarity and/or experience in common clinical practices, human physiology, or epidemiology of cardiovascular, metabolic, and renal disease areas is a plus.</li><li>Familiarity with or exposure to traditional drug discovery and development processes and approaches is a plus.</li></ul>Salary Base Salary: $163,616 to $184,000 This range represents the low and high end of the anticipated annual base salary range for the New York City based position. The actual annual base salary will depend on numerous factors such as: experience, knowledge, skills, and if the location of the job changes. More on Valo Valo Health, Inc ("Valo") is a technology company built to transform the drug discovery and development process using human-centric data and artificial intelligence-driven computation. As a digitally native company, Valo aims to fully integrate human-centric data across the entire drug development life cycle into a single unified architecture, thereby accelerating the discovery and development of life-changing drugs while simultaneously reducing costs, time, and failure rates. The company's Opal Computational Platform™ is an integrated set of capabilities designed to transform data into valuable insights that may accelerate discoveries and enable Valo to advance a robust pipeline of programs across cardiovascular metabolic renal, oncology, and neurodegenerative disease. Founded by Flagship Pioneering and headquartered in Boston, MA, Valo also has offices in Lexington, MA, and New York. To learn more, visit www.valohealth.com.

Data Scientist Valo Health Jobs

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Senior Data Scientist Clinical Informatics
April 12, 2024

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Data Scientist Valo Health Jobs

Staff Data Scientist Machine LearningApril 29, 2024

Staff Data Scientist Machine LearningApril 22, 2024

Staff Data Scientist Machine LearningApril 21, 2024

Senior Data Scientist Clinical InformaticsApril 21, 2024

Staff Data Scientist Machine LearningApril 18, 2024

Senior Data Scientist Clinical InformaticsApril 15, 2024

Senior Data Scientist Clinical InformaticsApril 12, 2024