As our Senior Data Scientist for our Startup Creation team, you will set up and configure the data infrastructure for our startups, and work with the startup founding team to define data driven KPIs, and implement automated statistical analyses of customer behavior.  Your goal is to make all of the companies that we launch data-driven from day one.

In this role, you will function as an in-house implementation team for the companies that Redesign Health launches (internally referred to as OpCos). We provide data strategy, data pipeline, data analytics and forecasting services to newly formed companies in a repeatable and scalable manner. Each engagement with an OpCo will interact directly with the founding team, and our team strives to both listen to their needs as operators, and help provide guidance on how to best use data in their decision making process. To execute on these projects you will work closely with the data engineering, engineering, marketing and strategy groups at Redesign Health.

You will report to and work with the Director of Data Science. The position can be fully remote within the United States or based out of our New York City headquarters.

What you'll do:

• Engage with key stakeholders
  
  • Work with venture chairs, CEOs, and Chief Product Officers
    Eliciting and synthesizing key requirements from OpCo founders.
    Engaging in a handoff that allows the OpCos to maintain and expand on the system provided
• Implement relevant aspects of our standard data stack
  
  • Integrate data from a variety of 3rd party data sources
    Provide data models for a single source of truth about all facets of a company and product
    Set up data transformations to provide reliable, aggregated data to dashboards
• Provide analyses tailored to each operating company
  
  • Rapidly learn about a domain within healthcare such as oncology, veterinary medicine, actuarial science, just to name a few.
  • Determine how these domain specific needs fit into common statistical analyses of behavior.
  • Implement robust statistical analyses as part of our data pipeline.
  • Provide automated actionable insights back to the OpCos in order to allow them to make critical business decisions in a data-driven manner.

What you'll need:

• Background
• 4-7 years of data engineering experience: SQL, ETL pipelines, metadata stores    
• 5+ years of data analytics experience: statistical analysis, data driven decision support, data-related SWOT analysis    
• 3+ years of experience working at a consulting firm or client services group

• Technical Skills
  • Ability to code in Python and SQL
  • Data Engineering: experience with ETL and integrating some sort of SaaS service (NetSuite, MixPanel, Iterable, etc.)
  • Strong experience setting up cloud architecture
  • Strong experience handling and understanding data sets    
  • Experience with data-driven decision making; ability to understand which data is relevant to a decision, and how to incorporate the presence or lack of data into a decision
  • Ability to define metrics and KPIs (financial KPIs, user behavior); ability to calculate churn, or LTV, things like CAC
  • Ability to configure dashboards and data visualization design 

• Behavioral Skills
  • Drives Results. Has a strong bottom-line orientation. Persists in accomplishing objectives despite obstacles and setbacks. Has a track record of exceeding goals successfully. Pushes self and helps others achieve results. Consistently achieving results, even under tough circumstances
  • Nimble Learning. Learns quickly when facing new situations. Experiments to find new solutions. Takes on the challenge of unfamiliar tasks. Extracts lessons learned from failures and mistakes. Learning through experimentation when tackling new problems, using both successes and failures as learning fodder

You will work out of one of the following locations:

• Remote: Alabama, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, District of Columbia, Florida, Georgia, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, Wyoming

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