Data Engineer, Encounters Intelligence

Team Mission

The Data Team is on a mission to represent medical reality by transforming raw data into assets that directly generate sales for our customers and help to bring cutting edge medical technology to the patients that need it most. We thrive on the challenge of turning complexity into simplicity and driving the continuous growth of our products. We acquire terabytes of data from diverse sources, and refine them with modern data processing tools and machine learning algorithms. This shapes the future of our products and delivers value to the customers.

Responsibilities

• Transform, model, and integrate raw data of varying quality from a wide range of data sources into usable, documented and high quality data and intelligence products by applying data modeling and statistical techniques
• Identify, research, and develop new statistical approaches and new types of data to improve and extend our core healthcare data products
• Lead feature and product development cycles from defining Customer problem statements through to delivering solutions
• Work directly with product managers and cross-functional stakeholders to influence and build our Product development plans and roadmap
• Provide thought leadership on data science techniques and mentoring to junior data engineers
• Document and communicate technical and quantitative concepts, schemas, and data product usage guidelines with appropriate levels of detail for internal and external stakeholders

Your Profile

• You have 4+ years of experience working in a data science or similar role, delivering analytic models as Data Products or Data Solutions
• You have professional experience working with time series, geospatial, and/or demographic datasets to make forecasts or predictions.
• You are excited by extracting signals and information from messy, real-world datasets
• You can translate and explain technical requirements, recommendations and code clearly and concisely for non-technical audiences.
• You are opinionated about statistical techniques and best practices