About us: 

At Ginger, we believe that everyone deserves access to incredible mental healthcare. Our on-demand system brings together behavioral health coaches, therapists, and psychiatrists, who work as a team to deliver personalized care, right through your smartphone. The Ginger app provides members with access to the support they need within seconds, 24/7, 365 days a year. Millions of people have access to Ginger through leading employers, health plans, and our network of partners.

Ginger has been recognized by The World Economic Forum as a Technology Pioneer and by Fast Company as one of the Most Innovative Companies in Healthcare. 

About the Role:

At Ginger, we aim to provide better mental health care to humanity at a scale larger than has ever been possible before. This is no small task and as an expanding team we are working on a number of initiatives to achieve this, including aggressively building tools to simultaneously grow our reach and improve quality of care.

What You'll Do:

Standing at the center of multiple teams (data science, engineering) and core systems, you'll..

• Open up our data to uncover important patterns at the level of individuals and sub-populations.
• Surface, serve and persist key actionable insights in mental health, healthy habit formation, goal pursuit, and care efficacy. 
• Help us scale our services using modern distributed processing tools and GPUs in the cloud (AWS)
• Collaborate with product to ideate and unlock features which derive as much actionable information from our data (text, media, activity etc) as possible.
• Help architect systems for near-real-time delivery of recommendations, care insights and other time-critical information to coaches and members. 
• Design lightweight data schemas appropriate for storing, organizing and joining processed communication and care analytics.
• Devise the tooling that takes us from algorithm prototype to production and can track data/model lineage and statistical drift through time.
• Develop pipelines that efficiently and reliably route output of machine learning algorithms to consumer processes and persistence mechanisms. 
• Own operational scalability of our algorithms, systems and data models.
• Stand up infrastructure for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Python and AWS tools.
• Work with a variety of stakeholders including the Data, Product, Engineering, Security and Executive teams to support their data accessibility needs.

Necessary Skills:

• Databases SQL/NoSQL 4+ years
• Cloud platform experience 3+ years
• SQL 4+ years
• Schema design 2+ years
• Amazon Web Services (AWS) 2+ years
• Deployment pipelines 2+ years
• Python 2+ years
• Deploying to production systems with active customers 2+ years 
• Distributed computing (e.g Spark, Hadoop etc.) 3+ years
• Infrastructure monitoring 1+ years
• Wide variety of data warehouse, data lake (s3) etc familiarity
• Analytics experience working with structured and unstructured data
• Project lead (self-managing) 1+ years
• Bachelors in technical field or experiential equivalent

Ideal Skills:

• Amazon Web Services (AWS) 3+ years
• AWS Lambda, Sagemaker
• Docker / Kubernetes
• DB performance engineering
• Machine Learning (ML) 1+ years
• Running ML on GPUs 1+ years
• Python 3+ years
• Strong analytics intuition grounded in significant experience 
• Experience in the healthcare space
• Masters in technical field or experiential equivalent