Data Scientist at Renew Health - CLOSED
Renew Health’s mission is to fundamentally transform how medications are managed in the health care system. To do so, we are building a modern and flexible tech stack that will anchor a highly differentiated approach to pharmacy benefits. This technology will power an innovative set of clinical services and exceptional member experience, which together can improve access, increase adherence, and ensure that members maximize the clinical benefit they receive from medications.
We believe that our approach will reduce population costs, decrease medication errors, and dramatically improve clinical outcomes. It will also allow us to align our business model with the interests of health plans and patients--passing through savings to clients and members, and generating revenue through clinical services that improve care and lower costs.
Our initial team of 30 includes co-founders of Oscar, Devoted, and Lyra Health, and alumni of top companies including Microsoft, Oracle, McKinsey, Snapchat, DaVita, AppNexus, and GoodRx. To date, Renew Health has raised $13M of funding, led by Venrock.
About the role:
An early member of the Data Science team that will lead high-impact projects, such as:
- Optimizing formulary design to improve medication adherence, reduce errors, and lower total cost of care
- Producing personalized, claims-based patient and provider risk assessment models to characterize and anticipate intervention needs
- Performing time series analysis of drug pricing to discover pricing inefficiencies
- BS or MS in STEM field (strong preference towards Math, Physics, Computer Science, Engineering) or Econometrics, PhD degree welcome
- 4+ years of experience outside of an academic setting
- 2+ years in a role as a Data Scientist; working knowledge of data mining and advanced analytics, using predictive modeling to solve business problems
- 1+ years in a role as a software engineer, data engineer, ML engineer, or equivalent; experience developing and testing software applications, developing ETL pipelines, and deploying code to production (strong preference towards Python for application code)
- Living near or willing to relocate to Los Angeles area
- Comfortable with common Python-based data science and visualization packages, including: pandas, numpy, matplotlib, plotly
- Experience driving research and development efforts and strong experimentation skills
- Ability to take software from research, to development, to production
- Experience with at least some of the following: hypothesis testing, data cleaning, natural language processing, image classification, anomaly detection, clustering, time series forecasting, neural networks, object-oriented programming, databases, unit testing, containerization, REST APIs, cloud computing, distributed systems or data visualization
- Knowledge of or experience with several of the following concepts: Linear & logistic regression, properties of distributions, statistical tests and proper usage, Bayesian Analysis, Time Series Analysis, Decision tree algorithms (e.g. random forest), Clustering algorithms (e.g. K-means), Support vector machine (SVM), Optimization techniques
- Positive attitude and great communication skills
- Comfortable with and willing to collaborate with both individual contributors, managers, and leadership across the company
- Knowledge of standard methods for measuring health care utilization, spending, quality, and outcomes