About Us: At Emendata, we help bridge the gap between data and the real world. We partner with organizations that have a social mission and help them tackle their problems using analytics. Our role in these partnerships goes end to end—we handle everything from wrangling the data to analyzing the problem to turning the results into something actionable. Importantly, we understand that this analytics pipeline does not live in a vacuum. Getting to meaningful numbers requires more than just the right methods; it calls for understanding the people, policies, data, and systems involved. With this approach, our small but fast-growing team is having a big impact, taking on challenges like using analytics to combat fraud, waste, and abuse in Medicare.

About the Role: For this role, we are looking for someone to serve as a technical lead on statistical projects analyzing healthcare programs. This position is responsible for translating high-level direction from management or clients into studies/analyses that leverage statistically robust methods. We are looking for you to:

  • Operationalize research questions from management and clients into robust analytic frameworks, research activities, and deliverables with minimal direction
  • Apply a broad set of statistical methods to analyze and interpret data, including survey data, health records, and other administrative data
  • Prepare research for dissemination to a variety of technical and non-technical audiences; produce materials (e.g., reports, presentations) that summarize the data and methodology, interpret analytic findings, and provide conclusions and recommendations
  • Support project teams internally by providing input on study design and application of statistical methods
  • Support development of data analysts through technical mentoring, code review, trainings, and other assistance
  • Continue growing subject matter expertise by staying up-to-date on the latest statistical techniques and applications; contribute to the development of the company’s institutional knowledge
  • Engage with stakeholders to understand client needs/priorities, business processes, program policy, data, etc. 

Required Qualifications: We are looking for you to have the following qualifications:

  • Education: M.S. or Ph.D. in statistics or related field
  • Experience: 2+ years applied research experience with statistical sampling and applying statistical models
  • Technical Expertise: Strong familiarity with statistical sampling, probability, regression modeling, and practical applications
  • Programming: Experience performing analyses using SAS, Python, Stata, R, or SQL 
  • Communication: Ability to write clearly and communicate effectively with technical and non-technical audiences
  • Interests: Strong interest in social science research
  • Working Style: Capable of working with minimal supervision and a high level of initiative; practical approach to problem-solving; comfortable working both independently and collaboratively on client-facing projects

Desired Qualifications: If you do not meet all the criteria below but still think you would be a good fit for this role, please apply so we can see if we can find the right spot for you on the team.

  • Experience: Strong track record of research excellence in a professional setting (experience in consulting preferred)
  • Technical Expertise: Familiarity with machine learning methods and practical applications a plus
  • Domain Expertise: Knowledge of healthcare data, policy, and program integrity efforts strongly preferred (e.g., Medicare policy, CMS data)

This position is full-time onsite in San Francisco. To be considered for this position, applicants must have the ability to work in the U.S. without a need for current or future visa sponsorship. Additionally, staff will be required to complete a successful background investigation, including the Questionnaire for Public Trust Position SF-85. Lastly, pursuant to the San Francisco Fair Chance Ordinance, all qualified applicants with arrest and conviction records will be considered for employment.

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