Data Scientist / Machine Learning Engineer

Data Scientist in New York, NY

Posted 2019-12-03


Well-funded stealth company focused on disrupting healthcare through a differentiated consumer experience and a world-class data & analytics engine to drive engagement and behavior change. The product will sell directly to Fortune 500 CEOs and full risk populations, integrating layers of analytics, digital, concierge services, behavioral health, telemedicine, care management and wellness services to drive sustained engagement, lower costs and improve health.

Reporting To

Head of Data Science and AI with dotted line to Chief Analytics and Marketing Officer

Position Summary

The overall goal is to engage consumers in differentiated ways that will drive better health outcomes. As one of the early hires of the Analytics organization, the primary mission will be to launch the modeling and optimization platform (the “Health Engine”) to deliver member recommendations that improve health, cost of delivery, and engagement.
You will leverage a wide range of disparate data sources across healthcare (member, payor, employer, provider, partner). Ideal candidates will have a detailed understanding of healthcare data with experience analyzing large longitudinal health datasets.
You will assist in the creation of operational predictive models using current and emerging methodologies in data science. Ideal candidates will possess a deep understanding of statistics, machine learning, causal predictive modeling, and most importantly, a willingness to grow deeper in these areas.
You will collaborate across the organization to drive projects from beginning to end: frame business questions, collect and analyze data, research, prototype, build pipelines, and share insights. You will work with engineering to ensure robust translation to production environments and create solutions that operate effectively at scale.
Minimum Qualifications

2+ years’ industry experience in data science or machine learning focused roles.
Advanced degree (MS or PhD) in a quantitative field such as Statistics, Computer Science, Mathematics, Physics, Engineering, Economics, or similar.
Demonstrated experience using Python for data analysis and machine learning (numpy, pandas, scikit-learn, xgboost, spacy, pytorch, stan/pymc3, etc.). Proficiency with SQL and databases. Experience using Unix/OSX from the command line, version control (git), and general software development best practices for contributing to a collaborative code base. Experience configuring and executing analyses in the cloud (GCP, AWS).
Strong communication and collaboration skills required. Ability to communicate technical modeling concepts and relevant aspects of modeling platforms to non-technical audiences.
Willingness to learn and improve across all technical skill areas and in knowledge of the healthcare domain. Ability to work in a start-up environment that is fast paced and maintain a focus on rapid prototyping of capabilities.

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