Grand Rounds is a new kind of healthcare company. Founded in 2011, the company is on a mission to raise the standard of healthcare for everyone, everywhere. The Grand Rounds team goes above and beyond to connect and guide people to the highest quality healthcare available for themselves and their loved ones. Grand Rounds creates products and services that give people the best possible healthcare experience. Named a 2019 Best Place to Work by Glassdoor and Rock Health’s 2018 Fastest Growing Company, Grand Rounds works with inspiring employers and doctors to empower them to be the change agents we need to make our shared vision a reality.
Data Scientists at Grand Rounds work on problems that are core to the company’s mission. Major challenges include developing systems and models to identify the highest quality doctors in the country as well as methodologies to uncover the subtle differences between each physician’s clinical expertise. Additionally, patient-level modeling allows us to understand the specific healthcare needs of every person. With a high fidelity understanding of both patients and physicians we are able to route patients to both appropriate and high quality care.
In addition to developing the company’s core technologies, data scientists provide decision support analysis for many teams across the organization including product development, sales, marketing, and strategy. Data scale ranges from small data sets that fit on a single laptop to large multi-terabyte clinical information in distributed database systems.
In your first 30 days, you will:
- Onboard with the Grand Rounds team in San Francisco, setup your dev environment, get access to data systems, and become familiar with the tech stack
- Learn about on-going initiatives involving data scientists, product managers, and engineers
- Spend time with members of the Analytics, Medical, and Patient Care teams and learn how our teams collaborate
- Become familiar with the data landscape and hit the ground running on a primary project
In your first 60 days, you will:
- Accelerate on-going development efforts around physician quality and expertise models
- Master the ins and outs of claims data: ICDs, CPTs, and all that
- Collaborate with engineers to improve the claims warehousing infrastructure
- Collaborate with engineers to develop a process/pipeline for model updates that seamlessly flows data to production systems
In your first 90 days, you will:
- Integrate into long-term multi-data-scientist ventures and deliver on one or several short-term individual projects
- Develop internal tools and codebases that are useful for other data scientists and/or engineers
- Spend time with Staff Physicians and other medical domain experts to learn about the world of healthcare
- Develop an understanding of both immediate business objectives as well as longer term company aspirations to develop intuition around prioritization and trade-offs between short-term deliverables and longer term R&D efforts
- Develop creative solutions to diverse problems including engineering challenges, unstructured data messes, ontology development, and machine learning applicationsLead and develop major projects from end-to-end encompassing planning, design, technical implementation, debugging, roll-out to Product & Engineering, testing, and iteration
- Operate at level of sophistication in statistics, machine learning, or computer science that is publication-worthy
- Regularly monitor pull requests, perform code reviews, and produce excellent peer reviews on projects prior to shipping to Product & Engineering
- Evaluate and experiment with new technologies and tools prior to wider adoption by the team
- Work closely with analysts, data scientists, product managers, and engineers
- Excellent verbal communications, including the ability to clearly and concisely articulate complex concepts to both technical and non-technical collaborators
- BS with 8+ years or MS with 6+ years or PhD with 3+ years of experience. Degree(s) should be in a technical discipline such as Computer Science, Engineering, Statistics, Physics, Math, quantitative social science
- Work experience as an engineer highly desired
- Experience with SQL relational databases as well as big data: the Hadoop ecosystem, Hive, Spark, Presto, Vertica, Greenplum, etc
- Required: SQL, Python, R, linux shell scripting
- Desired: Scala, Java, or Ruby
- Experience with machine learning and computational statistics packages (sci-kit learn, nltk, statsmodels, networkx, gephi, arules, glmnet, bigrf, caret, igraph, MLLib, GraphX, MADlib, Weka, etc)
- Experience with visualization tools (seaborn, d3, plotly, bokeh, ggplot2, rCharts, networkD3, Shiny, Tableau, CartoDB, etc)
- Frequent user of cloud computing platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform
- Bonus Points for: experience with web application frameworks (Shiny, Flask, Tkinter, Ruby on Rails, Pyramid, Django, etc)
- Double Bonus Points: previous work on medical applications and/or with claims data
This is a full time position located in San Francisco, CA.
Grand Rounds is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, state, or local law. Grand Rounds considers all qualified applicants in accordance with the San Francisco Fair Chance Ordinance.