Remote - U.S.
Who we are
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.
Ginger is a dynamic and fast growing startup with a forward-looking infrastructure and engineering systems landscape. Ginger operates its infrastructure in the top-class cloud IaaS and PaaS services and utilizes the best of the breed SaaS to power its business. There are many unique challenges and opportunities that are new to the industry and require creative thinking in order to balance the desire to continue to move fast and be nimble, and yet provide first-class privacy to the member's data and build unwavering trust with the members, customers and partners.
About the role
We are looking for an outstanding candidate that can immediately contribute to our product and is passionate about helping people be their best selves. You will be working closely with our data science, product, care, and customer success teams in particular. Key responsibilities will include building data models that provide relevant and intuitive analytics to both internal and external stakeholders.
- Work with organizations in Ginger to understand analytical needs, consult with your technical knowledge, build data models, and present analysis insights. Examples include:
- Working with coaching and clinical functions to address care-related quality assurance, measuring treatment effectiveness, assessing operational efficiency, forecasting both supply and demand.
- Teaming with product functions to better understand product engagement, feature use patterns, etc.
- Maintain and add to existing analytics infrastructure (Looker).
- Partner with machine learning engineers to validate and evaluate machine learning model outputs in both development and production environments, providing quantitative recommendations to stakeholders based on the evaluation.
- Develop expertise on mental healthcare data sets and lead their modeling to enable insights.
- Design experiments and determine appropriate statistical approaches to answer specific data science, product, clinical care or business questions.
- Foster a culture of broad access to data and autonomy in obtaining answers by implementing dashboards and other tools that helps your data customers extract, analyze, and visualize data easier and faster.
- Use appropriate tools (e.g. Python, R) to analyze and visualize data.
- MS with 1+ years of experience (or BS with 2+ years of experience) in statistics, data science or appropriate quantitative fields.
- Experience preparing, modeling, and transforming business data to better understand the needs and performance of the company.
- Experience with building visualizations, trend analysis, forecasts, statistical testing, and data-storytelling.
- Experience in analyzing data statistically using Python (preferred), R, Julia or Scala.
- Experience in querying large and complex SQL databases and doing ETL across systems and databases (Plus: Redshift, Spark/Hadoop, AWS).
- Development experience in business intelligence, data warehouses, and related technologies (Plus: Looker).
- Strong communication skills and business acumen - translate key metrics into the language of stakeholders , and contextualize results within the data customer’s domain.
- Strongly prefer someone with industry experience working with machine learning and data engineering teams, product teams, consumer marketing, or customer facing teams.