Data Scientist

NCQA is hiring! We are bringing depth to our research and analysis group, and we are looking for Data Scientist who are interested in health care and health policy to add to our growing organization.

The qualified candidate will conduct data analysis for various internal and external NCQA projects and use the analysis to interpret patterns of health care quality and potential health policy recommendations.

The qualified candidate will derive satisfaction and joy from translating large amounts of meta data into summaries, be naturally curious and invested in data or statistical methods, and have strong communicative and collaborative interests.

The experience expected from applicants, as well as additional skills and qualifications needed for this job are listed below.

Responsibilities :

• Present analytic results orally, develop PowerPoint presentations, and other documents in writing for internal and external customers, incorporating descriptions of methods, relevant literature, and other background material to provide context for the results.
• Independently and effectively conduct programming tasks and statistical analysis including preparation and cleaning of data, implementation and refinement of statistical methods, preparation of formatted tables of results, creation of databases and other outputs, and verification of the accuracy of results.
• Participate in quality assurance processes and review code, outputs tables, and charts. Complete all documentation and follow department standardized processes.
• Lead, design, plan, and execute programming approaches to support various development projects. Can code at an expert level in applications in SAS or R, able to quickly learn other coding languages as needed.
• Enhance NCQA reputation for data analysis in performance measurement through presentation at NCQA’s advisory meetings, publications, and other reports as requested.
• Support NCQA’s research and performance measurement activities by investigating data and developing data design and data structures related to the project.

Look at the data from different angles, determine what the data means and recommend the best viable way to analyze it. Spot trends and patterns and determine what is noise and what is good data.

In consultation with senior data scientists, support the development of analytical plans, such as database design, program design, selection of statistical methods, creation of project timelines, and development of formats for presenting results to meet customer needs.

Support the preparation of memos and close out reports to contribute to knowledge management and documentation.

Requirements :

• Master’s or Doctoral degree with experience in health services research, applied statistics, sociology, or a combination of education and experience which demonstrates the necessary skills and abilities required to succeed in data analysis.
• Strong programming skills in at least one of the following data coding languages - SAS, R, and SQL required. Certification a plus, knowledge of other statistical or data analysis programming languages a plus.

Working with claims-based data a plus.

• Strong programming background, 3 years (+) experience analyzing datasets.
• Proficiency in statistical software packages such as SAS, SPSS, STATA or R. Profound knowledge of word processing, spreadsheet, and database applications.

Skilled at developing and applying univariate and multivariate modeling techniques, hypothesis testing.

NCQA is committed to Diversity, Equity, and Inclusion. We are an Equal Opportunity Employer / Protected Veterans / Individuals with Disabilities.

NCQA is a drug-free workplace. NCQA recruits, hires, trains, and promotes individuals, and administers any and all personnel actions, without regard to race, color, religion, national origin, age, sex, pregnancy, citizenship, familial status, disability status, veteran status, genetic information, or other protected statuses under applicable state and federal laws.

NCQA will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant.

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