Staff Data Scientist, Machine Learning

March 21

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Valo Health

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Valo Health is a company dedicated to revolutionizing the discovery and development of life-changing medicines using high-quality patient data and AI-driven technology. Through its Opal Computational Platform, Valo Health integrates machine learning, tissue biology, and patient data to enhance drug discovery and development processes. The company brings together a diverse team of software engineers, data scientists, biologists, and chemists to harness advanced technology and patient data for innovative healthcare solutions. Valo Health is committed to achieving better health outcomes by accelerating the creation of medicines on behalf of patients worldwide.

51 - 200 employees

🧬 Biotechnology

🤖 Artificial Intelligence

⚕️ Healthcare Insurance

💰 Series C on 2022-10

📋 Description

• Valo Health is a technology company integrating human-centric data and AI for drug development. • As a Staff Data Scientist, you’ll design and apply ML models for scientific problems.

🎯 Requirements

• Degree in a quantitative field with 7+ (BS), 5+ (MS), or 3+ (PhD) years of post-degree experience or equivalent • Broad experience in ML including supervised learning, unsupervised learning, dimensionality reduction, clustering, metrics, model selection, feature selection, and explainability (3+ years required). • Demonstrated experience with ML on electronic health records (2+ years required). • Proficient in Python (5+ years required) and experience with ML and data science packages (e.g., scikit-learn, statsmodels, scipy, MLlib). • Experience with MLops methodology such as workflow orchestration (e.g., Airflow, Prefect), experiment tracking (e.g., MLflow), containerization (e.g., Docker), and reproducible research (3+ years required). • Experience with collaborative software development using source control management (e.g., git, unit testing, code review, CI/CD) (3+ years required). • Experience with large-scale data analytics engines (e.g., Spark or Dask) and working in cloud environments (e.g., AWS) (2+ years required). • 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.