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

🕒 May 15

🍂 Massachusetts – Remote

🍂 Massachusetts – Remote

💵 $165k - $190k / year

⏰ Full Time

🔴 Lead

📊 Data Scientist

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Valo Health

WebsiteLinkedInAll Job Openings

51 - 200 employees

🧬 Biotechnology

🤖 Artificial Intelligence

⚕️ Healthcare Insurance

💰 Series C on 2022-10

Biotechnology • Artificial Intelligence • Healthcare Insurance

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.

📋 Description

• lead the development of machine learning (ML) methods and analyses of patient data • perform project-specific hands-on analysis and modeling of high-dimensional longitudinal real-world data • contribute to the design, implementation, and evaluation of innovative machine learning approaches • articulate and break down large problems into solvable pieces • participate in code reviews and provide regular updates on work

🎯 Requirements

• MS, MPH, or PhD in health data science, biostatistics, or a related quantitative field with 5 years of experience developing and applying ML methods • 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.) • broad proficiency across core ML paradigms (e.g., supervised, unsupervised, semi-supervised) • strong grounding in key components of the ML development lifecycle • mastery of Python and modern data science tools (e.g., scikit-learn, PyTorch, statsmodels, SciPy, MLlib, MLflow) • exceptional time management, ability to prioritize multiple tasks simultaneously, and deliver products on time every time

🏖️ Benefits

• healthcare coverage • annual incentive program • retirement benefits • broad range of other benefits