Protenus is paving the way in healthcare with a leading, comprehensive approach to compliance analytics. Providing healthcare leaders full insight into how health data is being used, and alerting privacy, security and compliance teams to inappropriate activity, Protenus helps our partner hospitals make decisions about how to better protect their data, their patients, and their institutions. This year, Protenus was named one of Forbes' Best Startup Employers, one of the Best Places to Work in Healthcare and Family Friendliest Companies by Modern Healthcare, and certified as a Great Place to Work.

Senior Data Scientists at Protenus are experts at gleaning new insights from our data to drive the R&D of our current and future healthcare compliance analytics products. They act as strong, independent contributors capable of executing analytically intense tasks and relaying their findings in a concise, easy to understand form for stakeholders. Their work may inform product development and business strategy, or satisfy a sophisticated customer inquiry. They combine a curiosity for exploring data and testing new ideas, with analytical rigor which ensures the validity of their findings. Senior Data Scientists participate in a multi-disciplinary team consisting of Engineers, Product Managers, and other Data Scientists. They collaborate in this setting to ensure the rapid translation of research findings into product features or other assets for the company.

To learn more, read our employee spotlight here.

Responsibilities:

• Drive improvements in the functionality and accuracy of the analytics products
  • Take ownership of a specific research question, performing careful and rigorous work that is well documented and communicated within or across teams. Research questions range from optimizing an existing algorithm, to prototyping and evaluating a new functionality, to tuning and evaluating the performance of a classifier.
  • Translate a research finding into a specific plan for implementation.
  • Continuously identify areas for improvement, making sure that ideas are clearly captured in Jira or Confluence.
  • Provide feedback on other team members’ research with understanding of both the problem and how the solution can fit into the product.

• Suggest and communicate solutions to data science-related problems across teams
  • Understand data source and client specific differences in the analytics to support customer facing team members with customer questions and requests.
  • Troubleshoot analytics in production.
  • Provide support in mapping new data sources to the Protenus data model.

• Be technically proficient in the Protenus stack
  • Evaluate and communicate analytics in the context of business requirements.
  • Translate analytics into elegant, efficient code.
  • Identify issues or problems with others’ analytics/code through code review and research or design discussions.
  • Understand Protenus’ internal data models, what they contain, and where the data comes from.
  • Understand production environment and production data.

Key Qualifications, Skills, Competencies:

• Strong combination of academic background in a quantitative discipline combined with relevant industry experience. 
  • Bachelor’s + 8 years
  • Master’s + 5 years
  • PhD + 2 years
• Technical proficiency in development using Python or Scala, preferably atop a data framework or research platform (Jupyter Notebook, Spark). You don’t need to code like a software engineer, but should be comfortable reading code, authoring your own, and accepting feedback.
• Strong data visualization and story-telling skills.  Experience in presenting findings to audiences of varying backgrounds. You must be able to communicate your ideas succinctly, with your primary goal being to help others understand and act. 
• Strong background using statistics in an applied scientific setting (academia or industry). 
• Experience developing and improving multiple aspects of classification processes, including solid understanding of multiple machine learning techniques to inform algorithm selection and strong creativity and practicality in feature generation and classifier evaluation.
• Intellectually curious yet humble.  You know what you know, strive to know more and share what you find.
• Technical tools: Git, Bitbucket,  AWS, Mongo, Spark, Python, Scala. Productivity tools: JIRA, Confluence.

We value diversity on our team and firmly believe Protenus is stronger when we hire people who make their own unique contributions to our culture. We welcome all applicants and encourage candidates from underrepresented backgrounds to apply. Join our team to see how you can learn and grow with us.